Overview

Dataset statistics

Number of variables88
Number of observations55644
Missing cells275981
Missing cells (%)5.6%
Total size in memory37.8 MiB
Average record size in memory712.0 B

Variable types

Numeric75
Text12
Unsupported1

Alerts

vlan_id has constant value ""Constant
tunnel_id has constant value ""Constant
bidirectional_cwr_packets has constant value ""Constant
bidirectional_ece_packets has constant value ""Constant
bidirectional_urg_packets has constant value ""Constant
src2dst_cwr_packets has constant value ""Constant
src2dst_ece_packets has constant value ""Constant
src2dst_urg_packets has constant value ""Constant
dst2src_cwr_packets has constant value ""Constant
dst2src_ece_packets has constant value ""Constant
dst2src_urg_packets has constant value ""Constant
label has constant value ""Constant
requested_server_name has 55644 (100.0%) missing valuesMissing
client_fingerprint has 55284 (99.4%) missing valuesMissing
server_fingerprint has 54986 (98.8%) missing valuesMissing
user_agent has 55638 (> 99.9%) missing valuesMissing
content_type has 54429 (97.8%) missing valuesMissing
bidirectional_packets is highly skewed (γ1 = 126.8738661)Skewed
bidirectional_bytes is highly skewed (γ1 = 141.7673512)Skewed
src2dst_packets is highly skewed (γ1 = 146.4161178)Skewed
src2dst_bytes is highly skewed (γ1 = 154.8480015)Skewed
dst2src_packets is highly skewed (γ1 = 105.0447769)Skewed
dst2src_bytes is highly skewed (γ1 = 149.7628469)Skewed
dst2src_min_piat_ms is highly skewed (γ1 = 40.15911415)Skewed
dst2src_mean_piat_ms is highly skewed (γ1 = 27.27918207)Skewed
dst2src_stddev_piat_ms is highly skewed (γ1 = 29.81418431)Skewed
dst2src_max_piat_ms is highly skewed (γ1 = 25.8585379)Skewed
bidirectional_ack_packets is highly skewed (γ1 = 162.5517499)Skewed
bidirectional_psh_packets is highly skewed (γ1 = 148.6404399)Skewed
src2dst_ack_packets is highly skewed (γ1 = 174.5861689)Skewed
src2dst_psh_packets is highly skewed (γ1 = 63.14445639)Skewed
dst2src_ack_packets is highly skewed (γ1 = 135.2443851)Skewed
dst2src_psh_packets is highly skewed (γ1 = 159.4011725)Skewed
requested_server_name is an unsupported type, check if it needs cleaning or further analysisUnsupported
expiration_id has 54594 (98.1%) zerosZeros
src_port has 17984 (32.3%) zerosZeros
dst_port has 17984 (32.3%) zerosZeros
vlan_id has 55644 (100.0%) zerosZeros
tunnel_id has 55644 (100.0%) zerosZeros
bidirectional_duration_ms has 17333 (31.1%) zerosZeros
src2dst_duration_ms has 20436 (36.7%) zerosZeros
dst2src_first_seen_ms has 22660 (40.7%) zerosZeros
dst2src_last_seen_ms has 22660 (40.7%) zerosZeros
dst2src_duration_ms has 27306 (49.1%) zerosZeros
dst2src_packets has 22660 (40.7%) zerosZeros
dst2src_bytes has 22660 (40.7%) zerosZeros
bidirectional_stddev_ps has 26514 (47.6%) zerosZeros
src2dst_stddev_ps has 28515 (51.2%) zerosZeros
dst2src_min_ps has 22660 (40.7%) zerosZeros
dst2src_mean_ps has 22660 (40.7%) zerosZeros
dst2src_stddev_ps has 31430 (56.5%) zerosZeros
dst2src_max_ps has 22660 (40.7%) zerosZeros
bidirectional_min_piat_ms has 31630 (56.8%) zerosZeros
bidirectional_mean_piat_ms has 17333 (31.1%) zerosZeros
bidirectional_stddev_piat_ms has 22748 (40.9%) zerosZeros
bidirectional_max_piat_ms has 17333 (31.1%) zerosZeros
src2dst_min_piat_ms has 23044 (41.4%) zerosZeros
src2dst_mean_piat_ms has 20436 (36.7%) zerosZeros
src2dst_stddev_piat_ms has 25299 (45.5%) zerosZeros
src2dst_max_piat_ms has 20436 (36.7%) zerosZeros
dst2src_min_piat_ms has 29976 (53.9%) zerosZeros
dst2src_mean_piat_ms has 27306 (49.1%) zerosZeros
dst2src_stddev_piat_ms has 36326 (65.3%) zerosZeros
dst2src_max_piat_ms has 27306 (49.1%) zerosZeros
bidirectional_syn_packets has 29139 (52.4%) zerosZeros
bidirectional_cwr_packets has 55644 (100.0%) zerosZeros
bidirectional_ece_packets has 55644 (100.0%) zerosZeros
bidirectional_urg_packets has 55644 (100.0%) zerosZeros
bidirectional_ack_packets has 28206 (50.7%) zerosZeros
bidirectional_psh_packets has 52108 (93.6%) zerosZeros
bidirectional_rst_packets has 52996 (95.2%) zerosZeros
bidirectional_fin_packets has 31103 (55.9%) zerosZeros
src2dst_syn_packets has 29139 (52.4%) zerosZeros
src2dst_cwr_packets has 55644 (100.0%) zerosZeros
src2dst_ece_packets has 55644 (100.0%) zerosZeros
src2dst_urg_packets has 55644 (100.0%) zerosZeros
src2dst_ack_packets has 29610 (53.2%) zerosZeros
src2dst_psh_packets has 52749 (94.8%) zerosZeros
src2dst_rst_packets has 54150 (97.3%) zerosZeros
src2dst_fin_packets has 31806 (57.2%) zerosZeros
dst2src_syn_packets has 31230 (56.1%) zerosZeros
dst2src_cwr_packets has 55644 (100.0%) zerosZeros
dst2src_ece_packets has 55644 (100.0%) zerosZeros
dst2src_urg_packets has 55644 (100.0%) zerosZeros
dst2src_ack_packets has 28392 (51.0%) zerosZeros
dst2src_psh_packets has 52573 (94.5%) zerosZeros
dst2src_rst_packets has 54468 (97.9%) zerosZeros
dst2src_fin_packets has 31439 (56.5%) zerosZeros
application_is_guessed has 29801 (53.6%) zerosZeros
application_confidence has 1156 (2.1%) zerosZeros

Reproduction

Analysis started2023-06-05 18:15:05.926450
Analysis finished2023-06-05 18:15:08.183892
Duration2.26 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

Distinct39637
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23020.4686
Minimum0
Maximum74295
Zeros15
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:08.376601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1200.15
Q18168
median20233.5
Q334304
95-th percentile59527.15
Maximum74295
Range74295
Interquartile range (IQR)26136

Descriptive statistics

Standard deviation17544.99907
Coefficient of variation (CV)0.7621477814
Kurtosis-0.01876199009
Mean23020.4686
Median Absolute Deviation (MAD)12881.5
Skewness0.7673520547
Sum1280950955
Variance307826992.5
MonotonicityNot monotonic
2023-06-05T15:15:08.819185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
< 0.1%
1 14
 
< 0.1%
4 14
 
< 0.1%
2 13
 
< 0.1%
5 13
 
< 0.1%
2542 7
 
< 0.1%
7052 6
 
< 0.1%
8 6
 
< 0.1%
2403 6
 
< 0.1%
2330 6
 
< 0.1%
Other values (39627) 55544
99.8%
ValueCountFrequency (%)
0 15
< 0.1%
1 14
< 0.1%
2 13
< 0.1%
3 3
 
< 0.1%
4 14
< 0.1%
ValueCountFrequency (%)
74295 1
< 0.1%
74275 1
< 0.1%
74054 1
< 0.1%
74048 1
< 0.1%
74041 1
< 0.1%

id
Real number (ℝ)

Distinct39637
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23020.4686
Minimum0
Maximum74295
Zeros15
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:09.226300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1200.15
Q18168
median20233.5
Q334304
95-th percentile59527.15
Maximum74295
Range74295
Interquartile range (IQR)26136

Descriptive statistics

Standard deviation17544.99907
Coefficient of variation (CV)0.7621477814
Kurtosis-0.01876199009
Mean23020.4686
Median Absolute Deviation (MAD)12881.5
Skewness0.7673520547
Sum1280950955
Variance307826992.5
MonotonicityNot monotonic
2023-06-05T15:15:09.662153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
< 0.1%
1 14
 
< 0.1%
4 14
 
< 0.1%
2 13
 
< 0.1%
5 13
 
< 0.1%
2542 7
 
< 0.1%
7052 6
 
< 0.1%
8 6
 
< 0.1%
2403 6
 
< 0.1%
2330 6
 
< 0.1%
Other values (39627) 55544
99.8%
ValueCountFrequency (%)
0 15
< 0.1%
1 14
< 0.1%
2 13
< 0.1%
3 3
 
< 0.1%
4 14
< 0.1%
ValueCountFrequency (%)
74295 1
< 0.1%
74275 1
< 0.1%
74054 1
< 0.1%
74048 1
< 0.1%
74041 1
< 0.1%

expiration_id
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01886995903
Minimum0
Maximum1
Zeros54594
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:10.059066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1360669556
Coefficient of variation (CV)7.21077112
Kurtosis48.01794106
Mean0.01886995903
Median Absolute Deviation (MAD)0
Skewness7.072214304
Sum1050
Variance0.0185142164
MonotonicityNot monotonic
2023-06-05T15:15:10.415162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 54594
98.1%
1 1050
 
1.9%
ValueCountFrequency (%)
0 54594
98.1%
1 1050
 
1.9%
ValueCountFrequency (%)
1 1050
 
1.9%
0 54594
98.1%

src_ip
Text

Distinct625
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:10.812896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length24
Mean length14.53849472
Min length2

Characters and Unicode

Total characters808980
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique261 ?
Unique (%)0.5%

Sample

1st rowfe80::fc66:5abf:d63a:94fb
2nd rowfe80::fc66:5abf:d63a:94fb
3rd row192.168.1.191
4th row192.168.1.191
5th row192.168.1.191
ValueCountFrequency (%)
10.0.2.15 12552
22.6%
192.168.1.191 10995
19.8%
fe80::16cc:20ff:fe51:33ea 4363
 
7.8%
fe80::725a:fff:fee4:9bc0 3387
 
6.1%
192.168.1.192 3128
 
5.6%
192.168.1.240 2965
 
5.3%
10.0.0.46 2764
 
5.0%
192.168.1.249 1638
 
2.9%
fe80::72ee:50ff:fe18:3443 1481
 
2.7%
fe80::ee1a:59ff:fe83:2811 1317
 
2.4%
Other values (615) 11054
19.9%
2023-06-05T15:15:11.404043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 151243
18.7%
. 127431
15.8%
: 65741
8.1%
2 65425
8.1%
0 64074
7.9%
f 56577
 
7.0%
9 51375
 
6.4%
8 46474
 
5.7%
e 42166
 
5.2%
6 37573
 
4.6%
Other values (8) 100901
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485581
60.0%
Other Punctuation 193172
 
23.9%
Lowercase Letter 130227
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 151243
31.1%
2 65425
13.5%
0 64074
13.2%
9 51375
 
10.6%
8 46474
 
9.6%
6 37573
 
7.7%
5 25857
 
5.3%
4 17891
 
3.7%
3 17833
 
3.7%
7 7836
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
f 56577
43.4%
e 42166
32.4%
c 13115
 
10.1%
a 11374
 
8.7%
b 5698
 
4.4%
d 1297
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 127431
66.0%
: 65741
34.0%

Most occurring scripts

ValueCountFrequency (%)
Common 678753
83.9%
Latin 130227
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 151243
22.3%
. 127431
18.8%
: 65741
9.7%
2 65425
9.6%
0 64074
9.4%
9 51375
 
7.6%
8 46474
 
6.8%
6 37573
 
5.5%
5 25857
 
3.8%
4 17891
 
2.6%
Other values (2) 25669
 
3.8%
Latin
ValueCountFrequency (%)
f 56577
43.4%
e 42166
32.4%
c 13115
 
10.1%
a 11374
 
8.7%
b 5698
 
4.4%
d 1297
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 808980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 151243
18.7%
. 127431
15.8%
: 65741
8.1%
2 65425
8.1%
0 64074
7.9%
f 56577
 
7.0%
9 51375
 
6.4%
8 46474
 
5.7%
e 42166
 
5.2%
6 37573
 
4.6%
Other values (8) 100901
12.5%
Distinct37
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:11.844469image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters945948
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowd0:53:49:1b:0c:90
2nd rowd0:53:49:1b:0c:90
3rd row60:6c:66:cb:78:61
4th row60:6c:66:cb:78:61
5th row60:6c:66:cb:78:61
ValueCountFrequency (%)
08:00:27:a3:83:43 12863
23.1%
60:6c:66:cb:78:61 10995
19.8%
14:cc:20:51:33:ea 4952
 
8.9%
70:5a:0f:e4:9b:c0 4212
 
7.6%
00:62:6e:51:27:2e 3223
 
5.8%
44:65:0d:56:cc:d3 2965
 
5.3%
78:e4:00:6c:39:cd 2764
 
5.0%
00:16:6c:ab:6b:88 2587
 
4.6%
70:ee:50:18:34:43 2195
 
3.9%
ec:1a:59:79:f4:89 2167
 
3.9%
Other values (27) 6721
12.1%
2023-06-05T15:15:12.605018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 278220
29.4%
0 101821
 
10.8%
6 80082
 
8.5%
3 68007
 
7.2%
8 56077
 
5.9%
c 55620
 
5.9%
1 42183
 
4.5%
7 40459
 
4.3%
4 39548
 
4.2%
2 32869
 
3.5%
Other values (7) 151062
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 507097
53.6%
Other Punctuation 278220
29.4%
Lowercase Letter 160631
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101821
20.1%
6 80082
15.8%
3 68007
13.4%
8 56077
11.1%
1 42183
8.3%
7 40459
 
8.0%
4 39548
 
7.8%
2 32869
 
6.5%
5 28907
 
5.7%
9 17144
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
c 55620
34.6%
e 29282
18.2%
a 28872
18.0%
b 23517
14.6%
f 12020
 
7.5%
d 11320
 
7.0%
Other Punctuation
ValueCountFrequency (%)
: 278220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 785317
83.0%
Latin 160631
 
17.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 278220
35.4%
0 101821
 
13.0%
6 80082
 
10.2%
3 68007
 
8.7%
8 56077
 
7.1%
1 42183
 
5.4%
7 40459
 
5.2%
4 39548
 
5.0%
2 32869
 
4.2%
5 28907
 
3.7%
Latin
ValueCountFrequency (%)
c 55620
34.6%
e 29282
18.2%
a 28872
18.0%
b 23517
14.6%
f 12020
 
7.5%
d 11320
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 945948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 278220
29.4%
0 101821
 
10.8%
6 80082
 
8.5%
3 68007
 
7.2%
8 56077
 
5.9%
c 55620
 
5.9%
1 42183
 
4.5%
7 40459
 
4.3%
4 39548
 
4.2%
2 32869
 
3.5%
Other values (7) 151062
16.0%
Distinct32
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:13.013221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters445152
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowd0:53:49
2nd rowd0:53:49
3rd row60:6c:66
4th row60:6c:66
5th row60:6c:66
ValueCountFrequency (%)
08:00:27 12865
23.1%
60:6c:66 10995
19.8%
14:cc:20 4952
 
8.9%
70:5a:0f 4212
 
7.6%
ec:1a:59 3767
 
6.8%
00:62:6e 3223
 
5.8%
44:65:0d 2965
 
5.3%
78:e4:00 2764
 
5.0%
00:16:6c 2587
 
4.6%
70:ee:50 2422
 
4.4%
Other values (22) 4892
 
8.8%
2023-06-05T15:15:13.784677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 111288
25.0%
0 92345
20.7%
6 59905
13.5%
c 27949
 
6.3%
7 23771
 
5.3%
2 23511
 
5.3%
8 17131
 
3.8%
e 15716
 
3.5%
4 15178
 
3.4%
5 14578
 
3.3%
Other values (7) 43780
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 267878
60.2%
Other Punctuation 111288
25.0%
Lowercase Letter 65986
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92345
34.5%
6 59905
22.4%
7 23771
 
8.9%
2 23511
 
8.8%
8 17131
 
6.4%
4 15178
 
5.7%
5 14578
 
5.4%
1 13407
 
5.0%
9 4118
 
1.5%
3 3934
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
c 27949
42.4%
e 15716
23.8%
a 8198
 
12.4%
f 7848
 
11.9%
d 5470
 
8.3%
b 805
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 111288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 379166
85.2%
Latin 65986
 
14.8%

Most frequent character per script

Common
ValueCountFrequency (%)
: 111288
29.4%
0 92345
24.4%
6 59905
15.8%
7 23771
 
6.3%
2 23511
 
6.2%
8 17131
 
4.5%
4 15178
 
4.0%
5 14578
 
3.8%
1 13407
 
3.5%
9 4118
 
1.1%
Latin
ValueCountFrequency (%)
c 27949
42.4%
e 15716
23.8%
a 8198
 
12.4%
f 7848
 
11.9%
d 5470
 
8.3%
b 805
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 111288
25.0%
0 92345
20.7%
6 59905
13.5%
c 27949
 
6.3%
7 23771
 
5.3%
2 23511
 
5.3%
8 17131
 
3.8%
e 15716
 
3.5%
4 15178
 
3.4%
5 14578
 
3.3%
Other values (7) 43780
 
9.8%

src_port
Real number (ℝ)

Distinct16708
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30769.76511
Minimum0
Maximum65533
Zeros17984
Zeros (%)32.3%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:14.226078image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median41446.5
Q354794
95-th percentile59960
Maximum65533
Range65533
Interquartile range (IQR)54794

Descriptive statistics

Standard deviation25668.09359
Coefficient of variation (CV)0.8341985549
Kurtosis-1.768032299
Mean30769.76511
Median Absolute Deviation (MAD)17923.5
Skewness-0.2256173652
Sum1712152810
Variance658851028.7
MonotonicityNot monotonic
2023-06-05T15:15:14.654269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17984
32.3%
59370 2091
 
3.8%
80 889
 
1.6%
1900 593
 
1.1%
10001 591
 
1.1%
68 369
 
0.7%
59960 340
 
0.6%
48999 308
 
0.6%
443 297
 
0.5%
546 292
 
0.5%
Other values (16698) 31890
57.3%
ValueCountFrequency (%)
0 17984
32.3%
67 143
 
0.3%
68 369
 
0.7%
80 889
 
1.6%
123 20
 
< 0.1%
ValueCountFrequency (%)
65533 1
< 0.1%
65531 2
< 0.1%
65525 1
< 0.1%
65524 1
< 0.1%
65521 2
< 0.1%

dst_ip
Text

Distinct5480
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:15.158185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length24
Mean length12.71968227
Min length7

Characters and Unicode

Total characters707774
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1890 ?
Unique (%)3.4%

Sample

1st rowff02::1:2
2nd rowff02::1:2
3rd row192.168.33.254
4th row172.217.23.234
5th row172.217.23.234
ValueCountFrequency (%)
23.51.123.27 1628
 
2.9%
ff02::2 1313
 
2.4%
ff02::1:ff00:0 1305
 
2.3%
192.168.1.193 1274
 
2.3%
239.255.255.250 1211
 
2.2%
192.168.1.191 1042
 
1.9%
ff02::1:2 907
 
1.6%
93.184.216.34 898
 
1.6%
24.56.178.140 806
 
1.4%
255.255.255.255 797
 
1.4%
Other values (5470) 44463
79.9%
2023-06-05T15:15:16.117734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 127431
18.0%
1 109877
15.5%
2 98289
13.9%
0 48647
 
6.9%
5 42900
 
6.1%
: 42765
 
6.0%
f 41892
 
5.9%
3 39034
 
5.5%
4 32333
 
4.6%
9 31361
 
4.4%
Other values (8) 93245
13.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485663
68.6%
Other Punctuation 170196
 
24.0%
Lowercase Letter 51915
 
7.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 109877
22.6%
2 98289
20.2%
0 48647
10.0%
5 42900
 
8.8%
3 39034
 
8.0%
4 32333
 
6.7%
9 31361
 
6.5%
8 31178
 
6.4%
6 26779
 
5.5%
7 25265
 
5.2%
Lowercase Letter
ValueCountFrequency (%)
f 41892
80.7%
e 3418
 
6.6%
c 2726
 
5.3%
b 2568
 
4.9%
a 1263
 
2.4%
d 48
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 127431
74.9%
: 42765
 
25.1%

Most occurring scripts

ValueCountFrequency (%)
Common 655859
92.7%
Latin 51915
 
7.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 127431
19.4%
1 109877
16.8%
2 98289
15.0%
0 48647
 
7.4%
5 42900
 
6.5%
: 42765
 
6.5%
3 39034
 
6.0%
4 32333
 
4.9%
9 31361
 
4.8%
8 31178
 
4.8%
Other values (2) 52044
7.9%
Latin
ValueCountFrequency (%)
f 41892
80.7%
e 3418
 
6.6%
c 2726
 
5.3%
b 2568
 
4.9%
a 1263
 
2.4%
d 48
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 707774
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 127431
18.0%
1 109877
15.5%
2 98289
13.9%
0 48647
 
6.9%
5 42900
 
6.1%
: 42765
 
6.0%
f 41892
 
5.9%
3 39034
 
5.5%
4 32333
 
4.6%
9 31361
 
4.4%
Other values (8) 93245
13.2%
Distinct61
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:16.607896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters945948
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row33:33:00:01:00:02
2nd row33:33:00:01:00:02
3rd row00:13:33:b0:18:50
4th row00:13:33:b0:18:50
5th row00:13:33:b0:18:50
ValueCountFrequency (%)
52:54:00:12:35:02 12541
22.5%
00:13:33:b0:18:50 10995
19.8%
14:cc:20:51:33:ea 8285
14.9%
38:72:c0:5e:6b:22 2762
 
5.0%
33:33:00:00:00:02 1313
 
2.4%
33:33:ff:00:00:00 1305
 
2.3%
ec:1a:59:83:28:11 1274
 
2.3%
33:33:00:01:00:03 1240
 
2.2%
33:33:00:00:00:0c 1222
 
2.2%
01:00:5e:7f:ff:fa 1211
 
2.2%
Other values (51) 13496
24.3%
2023-06-05T15:15:17.467644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 278220
29.4%
0 166891
17.6%
3 125843
13.3%
1 67432
 
7.1%
5 65255
 
6.9%
2 60444
 
6.4%
f 34014
 
3.6%
c 27524
 
2.9%
4 24827
 
2.6%
8 23002
 
2.4%
Other values (7) 72496
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 553349
58.5%
Other Punctuation 278220
29.4%
Lowercase Letter 114379
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 166891
30.2%
3 125843
22.7%
1 67432
12.2%
5 65255
 
11.8%
2 60444
 
10.9%
4 24827
 
4.5%
8 23002
 
4.2%
6 9367
 
1.7%
7 6214
 
1.1%
9 4074
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
f 34014
29.7%
c 27524
24.1%
e 21025
18.4%
b 18983
16.6%
a 12291
 
10.7%
d 542
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 278220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 831569
87.9%
Latin 114379
 
12.1%

Most frequent character per script

Common
ValueCountFrequency (%)
: 278220
33.5%
0 166891
20.1%
3 125843
15.1%
1 67432
 
8.1%
5 65255
 
7.8%
2 60444
 
7.3%
4 24827
 
3.0%
8 23002
 
2.8%
6 9367
 
1.1%
7 6214
 
0.7%
Latin
ValueCountFrequency (%)
f 34014
29.7%
c 27524
24.1%
e 21025
18.4%
b 18983
16.6%
a 12291
 
10.7%
d 542
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 945948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 278220
29.4%
0 166891
17.6%
3 125843
13.3%
1 67432
 
7.1%
5 65255
 
6.9%
2 60444
 
6.4%
f 34014
 
3.6%
c 27524
 
2.9%
4 24827
 
2.6%
8 23002
 
2.4%
Other values (7) 72496
 
7.7%
Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:17.804617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters445152
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row33:33:00
2nd row33:33:00
3rd row00:13:33
4th row00:13:33
5th row00:13:33
ValueCountFrequency (%)
52:54:00 12541
22.5%
00:13:33 10995
19.8%
14:cc:20 8285
14.9%
33:33:ff 7095
12.8%
33:33:00 6042
10.9%
01:00:5e 3179
 
5.7%
38:72:c0 2762
 
5.0%
ec:1a:59 1276
 
2.3%
60:6c:66 1042
 
1.9%
ff:ff:ff 946
 
1.7%
Other values (17) 1481
 
2.7%
2023-06-05T15:15:18.465733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 111288
25.0%
3 88368
19.9%
0 82692
18.6%
5 29870
 
6.7%
1 24458
 
5.5%
2 24433
 
5.5%
c 21693
 
4.9%
4 21335
 
4.8%
f 20773
 
4.7%
e 5915
 
1.3%
Other values (7) 14327
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283913
63.8%
Other Punctuation 111288
 
25.0%
Lowercase Letter 49951
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 88368
31.1%
0 82692
29.1%
5 29870
 
10.5%
1 24458
 
8.6%
2 24433
 
8.6%
4 21335
 
7.5%
6 4336
 
1.5%
8 3765
 
1.3%
7 3342
 
1.2%
9 1314
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
c 21693
43.4%
f 20773
41.6%
e 5915
 
11.8%
a 1284
 
2.6%
d 201
 
0.4%
b 85
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 111288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 395201
88.8%
Latin 49951
 
11.2%

Most frequent character per script

Common
ValueCountFrequency (%)
: 111288
28.2%
3 88368
22.4%
0 82692
20.9%
5 29870
 
7.6%
1 24458
 
6.2%
2 24433
 
6.2%
4 21335
 
5.4%
6 4336
 
1.1%
8 3765
 
1.0%
7 3342
 
0.8%
Latin
ValueCountFrequency (%)
c 21693
43.4%
f 20773
41.6%
e 5915
 
11.8%
a 1284
 
2.6%
d 201
 
0.4%
b 85
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 111288
25.0%
3 88368
19.9%
0 82692
18.6%
5 29870
 
6.7%
1 24458
 
5.5%
2 24433
 
5.5%
c 21693
 
4.9%
4 21335
 
4.8%
f 20773
 
4.7%
e 5915
 
1.3%
Other values (7) 14327
 
3.2%

dst_port
Real number (ℝ)

Distinct2563
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4438.414366
Minimum0
Maximum65502
Zeros17984
Zeros (%)32.3%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:18.901331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median80
Q3123
95-th percentile44403
Maximum65502
Range65502
Interquartile range (IQR)123

Descriptive statistics

Standard deviation12992.55769
Coefficient of variation (CV)2.927297143
Kurtosis8.499098758
Mean4438.414366
Median Absolute Deviation (MAD)80
Skewness3.124789831
Sum246971129
Variance168806555.4
MonotonicityNot monotonic
2023-06-05T15:15:19.328574image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 22746
40.9%
0 17984
32.3%
123 3031
 
5.4%
443 1883
 
3.4%
3080 1274
 
2.3%
10000 595
 
1.1%
50443 427
 
0.8%
67 369
 
0.7%
10001 338
 
0.6%
3478 318
 
0.6%
Other values (2553) 6679
 
12.0%
ValueCountFrequency (%)
0 17984
32.3%
7 1
 
< 0.1%
22 1
 
< 0.1%
67 369
 
0.7%
68 143
 
0.3%
ValueCountFrequency (%)
65502 1
< 0.1%
65173 2
< 0.1%
65035 2
< 0.1%
64964 2
< 0.1%
64913 2
< 0.1%

protocol
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.51252606
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:19.707335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median6
Q317
95-th percentile58
Maximum58
Range57
Interquartile range (IQR)11

Descriptive statistics

Standard deviation21.56424172
Coefficient of variation (CV)1.105148644
Kurtosis-0.5331121373
Mean19.51252606
Median Absolute Deviation (MAD)0
Skewness1.136940237
Sum1085755
Variance465.0165208
MonotonicityNot monotonic
2023-06-05T15:15:20.042842image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
6 28058
50.4%
58 12860
23.1%
17 9602
 
17.3%
2 3169
 
5.7%
1 1955
 
3.5%
ValueCountFrequency (%)
1 1955
 
3.5%
2 3169
 
5.7%
6 28058
50.4%
17 9602
 
17.3%
58 12860
23.1%
ValueCountFrequency (%)
58 12860
23.1%
17 9602
 
17.3%
6 28058
50.4%
2 3169
 
5.7%
1 1955
 
3.5%

ip_version
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.473258572
Minimum4
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:20.405080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q14
median4
Q34
95-th percentile6
Maximum6
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8500332074
Coefficient of variation (CV)0.1900255024
Kurtosis-0.4639347475
Mean4.473258572
Median Absolute Deviation (MAD)0
Skewness1.239387723
Sum248910
Variance0.7225564537
MonotonicityNot monotonic
2023-06-05T15:15:20.754877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
4 42477
76.3%
6 13167
 
23.7%
ValueCountFrequency (%)
4 42477
76.3%
6 13167
 
23.7%
ValueCountFrequency (%)
6 13167
 
23.7%
4 42477
76.3%

vlan_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:21.124779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:21.460927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

tunnel_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:21.806542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:22.140800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
Distinct48949
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.132581206 × 1012
Minimum7392
Maximum1.493732834 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:22.539235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile2082800.95
Q11.387315105 × 1012
median1.475197757 × 1012
Q31.475238147 × 1012
95-th percentile1.493731451 × 1012
Maximum1.493732834 × 1012
Range1.493732827 × 1012
Interquartile range (IQR)8.792304229 × 1010

Descriptive statistics

Standard deviation6.225266816 × 1011
Coefficient of variation (CV)0.5496530212
Kurtosis-0.3886291472
Mean1.132581206 × 1012
Median Absolute Deviation (MAD)1.85290059 × 1010
Skewness-1.266875661
Sum6.302134863 × 1016
Variance3.875394693 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:22.981576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49373175 × 101224
 
< 0.1%
1.493730733 × 101219
 
< 0.1%
1.49373175 × 101217
 
< 0.1%
1.493731161 × 101217
 
< 0.1%
1.493730732 × 101216
 
< 0.1%
1.493728079 × 101215
 
< 0.1%
1.493729182 × 101215
 
< 0.1%
1.493728993 × 101214
 
< 0.1%
1.493730733 × 101214
 
< 0.1%
1.493731052 × 101214
 
< 0.1%
Other values (48939) 55479
99.7%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13159 1
< 0.1%
14160 1
< 0.1%
30507 1
< 0.1%
ValueCountFrequency (%)
1.493732834 × 10121
 
< 0.1%
1.493732834 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10123
< 0.1%
Distinct50621
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.132581255 × 1012
Minimum14160
Maximum1.493732969 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:23.597498image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum14160
5-th percentile2095498.35
Q11.387315108 × 1012
median1.475197871 × 1012
Q31.475238247 × 1012
95-th percentile1.493731457 × 1012
Maximum1.493732969 × 1012
Range1.493732955 × 1012
Interquartile range (IQR)8.792313915 × 1010

Descriptive statistics

Standard deviation6.225266958 × 1011
Coefficient of variation (CV)0.54965301
Kurtosis-0.3886291463
Mean1.132581255 × 1012
Median Absolute Deviation (MAD)1.852889561 × 1010
Skewness-1.266875663
Sum6.302135135 × 1016
Variance3.87539487 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:23.848943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493728087 × 101215
 
< 0.1%
1.493731028 × 101215
 
< 0.1%
1.493728071 × 101213
 
< 0.1%
1.493728072 × 101210
 
< 0.1%
1.493727074 × 101210
 
< 0.1%
1.493728071 × 10129
 
< 0.1%
1.493729276 × 10129
 
< 0.1%
1.493730788 × 10129
 
< 0.1%
1.387314964 × 10128
 
< 0.1%
1.49372792 × 10128
 
< 0.1%
Other values (50611) 55538
99.8%
ValueCountFrequency (%)
14160 1
< 0.1%
15161 1
< 0.1%
20650 1
< 0.1%
40491 1
< 0.1%
40991 1
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

bidirectional_duration_ms
Real number (ℝ)

Distinct13678
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48953.10975
Minimum0
Maximum1799999
Zeros17333
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:24.204194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1123.5
Q36660
95-th percentile118268
Maximum1799999
Range1799999
Interquartile range (IQR)6660

Descriptive statistics

Standard deviation258976.4877
Coefficient of variation (CV)5.29029696
Kurtosis39.11712364
Mean48953.10975
Median Absolute Deviation (MAD)1123.5
Skewness6.350376335
Sum2723946839
Variance6.706882117 × 1010
MonotonicityNot monotonic
2023-06-05T15:15:24.647547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17333
31.1%
145 182
 
0.3%
2020 152
 
0.3%
2021 143
 
0.3%
153 129
 
0.2%
197 128
 
0.2%
228 120
 
0.2%
2 109
 
0.2%
154 108
 
0.2%
1 99
 
0.2%
Other values (13668) 37141
66.7%
ValueCountFrequency (%)
0 17333
31.1%
1 99
 
0.2%
2 109
 
0.2%
3 63
 
0.1%
4 31
 
0.1%
ValueCountFrequency (%)
1799999 6
< 0.1%
1799998 1
 
< 0.1%
1799997 1
 
< 0.1%
1799996 1
 
< 0.1%
1799995 2
 
< 0.1%

bidirectional_packets
Real number (ℝ)

Distinct416
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.5332291
Minimum1
Maximum392213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:25.101862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q37
95-th percentile20
Maximum392213
Range392212
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2241.353415
Coefficient of variation (CV)59.71650903
Kurtosis19052.72779
Mean37.5332291
Median Absolute Deviation (MAD)3
Skewness126.8738661
Sum2088499
Variance5023665.129
MonotonicityNot monotonic
2023-06-05T15:15:25.543725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 17221
30.9%
7 12272
22.1%
6 8756
15.7%
2 5377
 
9.7%
3 2392
 
4.3%
4 1664
 
3.0%
8 1168
 
2.1%
5 1121
 
2.0%
10 868
 
1.6%
9 627
 
1.1%
Other values (406) 4178
 
7.5%
ValueCountFrequency (%)
1 17221
30.9%
2 5377
 
9.7%
3 2392
 
4.3%
4 1664
 
3.0%
5 1121
 
2.0%
ValueCountFrequency (%)
392213 1
< 0.1%
184518 2
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%
16236 2
< 0.1%

bidirectional_bytes
Real number (ℝ)

Distinct2800
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24550.33709
Minimum46
Maximum424668890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:25.903235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q186
median390
Q3412
95-th percentile3363
Maximum424668890
Range424668844
Interquartile range (IQR)326

Descriptive statistics

Standard deviation2251167.888
Coefficient of variation (CV)91.69600725
Kurtosis24013.43193
Mean24550.33709
Median Absolute Deviation (MAD)210
Skewness141.7673512
Sum1366078957
Variance5.067756859 × 1012
MonotonicityNot monotonic
2023-06-05T15:15:26.338583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 11495
20.7%
408 6186
 
11.1%
390 5545
 
10.0%
394 4870
 
8.8%
46 2383
 
4.3%
180 1626
 
2.9%
172 1203
 
2.2%
412 1041
 
1.9%
143 952
 
1.7%
474 680
 
1.2%
Other values (2790) 19663
35.3%
ValueCountFrequency (%)
46 2383
4.3%
54 7
 
< 0.1%
55 96
 
0.2%
60 544
 
1.0%
62 77
 
0.1%
ValueCountFrequency (%)
424668890 1
< 0.1%
148005382 2
< 0.1%
128190733 2
< 0.1%
110825666 2
< 0.1%
13090548 2
< 0.1%

src2dst_first_seen_ms
Real number (ℝ)

Distinct48949
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.132581206 × 1012
Minimum7392
Maximum1.493732834 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:26.653207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile2082800.95
Q11.387315105 × 1012
median1.475197757 × 1012
Q31.475238147 × 1012
95-th percentile1.493731451 × 1012
Maximum1.493732834 × 1012
Range1.493732827 × 1012
Interquartile range (IQR)8.792304229 × 1010

Descriptive statistics

Standard deviation6.225266816 × 1011
Coefficient of variation (CV)0.5496530212
Kurtosis-0.3886291472
Mean1.132581206 × 1012
Median Absolute Deviation (MAD)1.85290059 × 1010
Skewness-1.266875661
Sum6.302134863 × 1016
Variance3.875394693 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:26.901974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49373175 × 101224
 
< 0.1%
1.493730733 × 101219
 
< 0.1%
1.49373175 × 101217
 
< 0.1%
1.493731161 × 101217
 
< 0.1%
1.493730732 × 101216
 
< 0.1%
1.493728079 × 101215
 
< 0.1%
1.493729182 × 101215
 
< 0.1%
1.493728993 × 101214
 
< 0.1%
1.493730733 × 101214
 
< 0.1%
1.493731052 × 101214
 
< 0.1%
Other values (48939) 55479
99.7%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13159 1
< 0.1%
14160 1
< 0.1%
30507 1
< 0.1%
ValueCountFrequency (%)
1.493732834 × 10121
 
< 0.1%
1.493732834 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10121
 
< 0.1%
1.493732824 × 10123
< 0.1%

src2dst_last_seen_ms
Real number (ℝ)

Distinct50408
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.132581255 × 1012
Minimum14160
Maximum1.493732969 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:27.328991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum14160
5-th percentile2095498.35
Q11.387315107 × 1012
median1.475197871 × 1012
Q31.475238247 × 1012
95-th percentile1.493731457 × 1012
Maximum1.493732969 × 1012
Range1.493732955 × 1012
Interquartile range (IQR)8.792313951 × 1010

Descriptive statistics

Standard deviation6.225266958 × 1011
Coefficient of variation (CV)0.54965301
Kurtosis-0.3886291463
Mean1.132581255 × 1012
Median Absolute Deviation (MAD)1.852889568 × 1010
Skewness-1.266875663
Sum6.302135134 × 1016
Variance3.87539487 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:27.774135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.387315073 × 101216
 
< 0.1%
1.493731028 × 101215
 
< 0.1%
1.493728087 × 101214
 
< 0.1%
1.493727256 × 101213
 
< 0.1%
1.493727967 × 101211
 
< 0.1%
1.387315713 × 101210
 
< 0.1%
1.387315523 × 101210
 
< 0.1%
1.493727074 × 101210
 
< 0.1%
1.387315663 × 101210
 
< 0.1%
1.387315238 × 101210
 
< 0.1%
Other values (50398) 55525
99.8%
ValueCountFrequency (%)
14160 1
< 0.1%
15161 1
< 0.1%
20650 1
< 0.1%
40491 1
< 0.1%
40991 1
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

src2dst_duration_ms
Real number (ℝ)

Distinct13322
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48852.44017
Minimum0
Maximum1799999
Zeros20436
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:28.118181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1008
Q36624
95-th percentile118268
Maximum1799999
Range1799999
Interquartile range (IQR)6624

Descriptive statistics

Standard deviation258910.7837
Coefficient of variation (CV)5.299853657
Kurtosis39.1352123
Mean48852.44017
Median Absolute Deviation (MAD)1008
Skewness6.35211545
Sum2718345181
Variance6.703479391 × 1010
MonotonicityNot monotonic
2023-06-05T15:15:28.528060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20436
36.7%
2020 152
 
0.3%
2021 146
 
0.3%
1 96
 
0.2%
2022 96
 
0.2%
307 87
 
0.2%
18 85
 
0.2%
147 79
 
0.1%
2002 79
 
0.1%
308 79
 
0.1%
Other values (13312) 34309
61.7%
ValueCountFrequency (%)
0 20436
36.7%
1 96
 
0.2%
2 70
 
0.1%
3 42
 
0.1%
4 21
 
< 0.1%
ValueCountFrequency (%)
1799999 6
< 0.1%
1799998 1
 
< 0.1%
1799997 1
 
< 0.1%
1799995 1
 
< 0.1%
1799993 1
 
< 0.1%

src2dst_packets
Real number (ℝ)

Distinct297
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.817213
Minimum1
Maximum271835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:28.964249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile10
Maximum271835
Range271834
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1425.143914
Coefficient of variation (CV)65.32199666
Kurtosis25202.5196
Mean21.817213
Median Absolute Deviation (MAD)1
Skewness146.4161178
Sum1213997
Variance2031035.177
MonotonicityNot monotonic
2023-06-05T15:15:29.251082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 20330
36.5%
4 19703
35.4%
2 4639
 
8.3%
3 3695
 
6.6%
5 2075
 
3.7%
7 816
 
1.5%
6 599
 
1.1%
10 583
 
1.0%
8 355
 
0.6%
46 213
 
0.4%
Other values (287) 2636
 
4.7%
ValueCountFrequency (%)
1 20330
36.5%
2 4639
 
8.3%
3 3695
 
6.6%
4 19703
35.4%
5 2075
 
3.7%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
91724 2
< 0.1%
36078 2
< 0.1%
9702 2
< 0.1%

src2dst_bytes
Real number (ℝ)

Distinct2003
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18022.18511
Minimum46
Maximum383809522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:29.594208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q186
median224
Q3272
95-th percentile1404.4
Maximum383809522
Range383809476
Interquartile range (IQR)186

Descriptive statistics

Standard deviation1966642.887
Coefficient of variation (CV)109.1234429
Kurtosis27529.75857
Mean18022.18511
Median Absolute Deviation (MAD)84
Skewness154.8480015
Sum1002826468
Variance3.867684246 × 1012
MonotonicityNot monotonic
2023-06-05T15:15:29.862361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 11495
20.7%
272 8424
15.1%
224 5543
 
10.0%
228 4872
 
8.8%
46 2383
 
4.3%
143 1828
 
3.3%
270 1484
 
2.7%
90 1431
 
2.6%
172 1210
 
2.2%
206 1021
 
1.8%
Other values (1993) 15953
28.7%
ValueCountFrequency (%)
46 2383
4.3%
54 19
 
< 0.1%
55 96
 
0.2%
60 544
 
1.0%
62 77
 
0.1%
ValueCountFrequency (%)
383809522 1
< 0.1%
146054307 2
< 0.1%
111505374 2
< 0.1%
12644847 2
< 0.1%
5898809 1
< 0.1%

dst2src_first_seen_ms
Real number (ℝ)

Distinct29035
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.537989689 × 1011
Minimum0
Maximum1.493732856 × 1012
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:30.158431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4993847
Q31.475220366 × 1012
95-th percentile1.493731436 × 1012
Maximum1.493732856 × 1012
Range1.493732856 × 1012
Interquartile range (IQR)1.475220366 × 1012

Descriptive statistics

Standard deviation7.160724999 × 1011
Coefficient of variation (CV)1.293018839
Kurtosis-1.72677539
Mean5.537989689 × 1011
Median Absolute Deviation (MAD)4993847
Skewness0.5207256649
Sum3.081558983 × 1016
Variance5.127598251 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:30.567042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
3793598 8
 
< 0.1%
1.493728803 × 10127
 
< 0.1%
1.493726611 × 10127
 
< 0.1%
1.493731477 × 10127
 
< 0.1%
1.493731752 × 10127
 
< 0.1%
338249 7
 
< 0.1%
1.493729117 × 10127
 
< 0.1%
1.493727914 × 10127
 
< 0.1%
1.49372793 × 10126
 
< 0.1%
Other values (29025) 32921
59.2%
ValueCountFrequency (%)
0 22660
40.7%
12401 1
 
< 0.1%
13159 1
 
< 0.1%
14160 1
 
< 0.1%
35521 1
 
< 0.1%
ValueCountFrequency (%)
1.493732856 × 10121
< 0.1%
1.493732837 × 10121
< 0.1%
1.493732834 × 10121
< 0.1%
1.493732834 × 10121
< 0.1%
1.493732824 × 10121
< 0.1%

dst2src_last_seen_ms
Real number (ℝ)

Distinct28413
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.537990042 × 1011
Minimum0
Maximum1.493732969 × 1012
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:30.969363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5008489
Q31.475220459 × 1012
95-th percentile1.49373144 × 1012
Maximum1.493732969 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)1.475220459 × 1012

Descriptive statistics

Standard deviation7.160725357 × 1011
Coefficient of variation (CV)1.293018821
Kurtosis-1.726775396
Mean5.537990042 × 1011
Median Absolute Deviation (MAD)5008489
Skewness0.5207256624
Sum3.081559179 × 1016
Variance5.127598764 × 1023
MonotonicityNot monotonic
2023-06-05T15:15:31.391277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
1.493731028 × 101215
 
< 0.1%
1.493727074 × 10129
 
< 0.1%
13569002 9
 
< 0.1%
393486 8
 
< 0.1%
269212 8
 
< 0.1%
7618218 8
 
< 0.1%
1.49373074 × 10127
 
< 0.1%
1.493728071 × 10127
 
< 0.1%
3614855 7
 
< 0.1%
Other values (28403) 32906
59.1%
ValueCountFrequency (%)
0 22660
40.7%
14160 1
 
< 0.1%
15161 1
 
< 0.1%
56256 1
 
< 0.1%
56905 1
 
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732897 × 10121
< 0.1%
1.493732894 × 10121
< 0.1%

dst2src_duration_ms
Real number (ℝ)

Distinct10691
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35296.84643
Minimum0
Maximum1799978
Zeros27306
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:32.047468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20
Q35862
95-th percentile13303.85
Maximum1799978
Range1799978
Interquartile range (IQR)5862

Descriptive statistics

Standard deviation229174.8218
Coefficient of variation (CV)6.492784625
Kurtosis51.7430403
Mean35296.84643
Median Absolute Deviation (MAD)20
Skewness7.286189987
Sum1964057723
Variance5.252109897 × 1010
MonotonicityNot monotonic
2023-06-05T15:15:32.493526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27306
49.1%
155 95
 
0.2%
18 88
 
0.2%
146 85
 
0.2%
2002 83
 
0.1%
156 82
 
0.1%
147 79
 
0.1%
148 77
 
0.1%
1008 76
 
0.1%
157 70
 
0.1%
Other values (10681) 27603
49.6%
ValueCountFrequency (%)
0 27306
49.1%
1 18
 
< 0.1%
2 4
 
< 0.1%
3 58
 
0.1%
4 23
 
< 0.1%
ValueCountFrequency (%)
1799978 1
< 0.1%
1799966 1
< 0.1%
1799918 1
< 0.1%
1799917 1
< 0.1%
1799884 1
< 0.1%

dst2src_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct303
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.7160161
Minimum0
Maximum120378
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:32.929599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile8
Maximum120378
Range120378
Interquartile range (IQR)3

Descriptive statistics

Standard deviation896.4395807
Coefficient of variation (CV)57.03987415
Kurtosis11710.12078
Mean15.7160161
Median Absolute Deviation (MAD)2
Skewness105.0447769
Sum874502
Variance803603.9218
MonotonicityNot monotonic
2023-06-05T15:15:33.352857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
3 14205
25.5%
2 8888
 
16.0%
1 4623
 
8.3%
5 895
 
1.6%
4 838
 
1.5%
10 525
 
0.9%
6 301
 
0.5%
7 285
 
0.5%
8 209
 
0.4%
Other values (293) 2215
 
4.0%
ValueCountFrequency (%)
0 22660
40.7%
1 4623
 
8.3%
2 8888
 
16.0%
3 14205
25.5%
4 838
 
1.5%
ValueCountFrequency (%)
120378 1
< 0.1%
92794 2
< 0.1%
74533 2
< 0.1%
27275 2
< 0.1%
6534 2
< 0.1%

dst2src_bytes
Real number (ℝ)

SKEWED  ZEROS 

Distinct2113
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6528.151984
Minimum0
Maximum108240611
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:33.791207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median136
Q3166
95-th percentile980
Maximum108240611
Range108240611
Interquartile range (IQR)166

Descriptive statistics

Standard deviation679410.274
Coefficient of variation (CV)104.0739057
Kurtosis23397.31508
Mean6528.151984
Median Absolute Deviation (MAD)136
Skewness149.7628469
Sum363252489
Variance4.615983205 × 1011
MonotonicityNot monotonic
2023-06-05T15:15:34.169177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
166 11115
20.0%
136 6920
 
12.4%
90 1470
 
2.6%
140 960
 
1.7%
202 790
 
1.4%
58 745
 
1.3%
206 725
 
1.3%
270 710
 
1.3%
490 563
 
1.0%
Other values (2103) 8986
 
16.1%
ValueCountFrequency (%)
0 22660
40.7%
54 389
 
0.7%
58 745
 
1.3%
62 1
 
< 0.1%
66 165
 
0.3%
ValueCountFrequency (%)
108240611 2
< 0.1%
40859368 1
< 0.1%
16685359 2
< 0.1%
2108308 1
< 0.1%
1951075 2
< 0.1%

bidirectional_min_ps
Real number (ℝ)

Distinct107
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.53624829
Minimum43
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:34.425972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile54
Q154
median66
Q386
95-th percentile148
Maximum590
Range547
Interquartile range (IQR)32

Descriptive statistics

Standard deviation56.13641051
Coefficient of variation (CV)0.6720006184
Kurtosis17.50651447
Mean83.53624829
Median Absolute Deviation (MAD)12
Skewness4.013026206
Sum4648291
Variance3151.296585
MonotonicityNot monotonic
2023-06-05T15:15:34.663366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 14455
26.0%
66 12958
23.3%
86 12755
22.9%
90 3083
 
5.5%
46 2513
 
4.5%
143 1948
 
3.5%
98 1451
 
2.6%
350 776
 
1.4%
60 617
 
1.1%
163 594
 
1.1%
Other values (97) 4494
 
8.1%
ValueCountFrequency (%)
43 48
 
0.1%
46 2513
 
4.5%
54 14455
26.0%
55 96
 
0.2%
56 1
 
< 0.1%
ValueCountFrequency (%)
590 11
< 0.1%
512 1
 
< 0.1%
506 1
 
< 0.1%
467 1
 
< 0.1%
453 23
< 0.1%

bidirectional_mean_ps
Real number (ℝ)

Distinct2885
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.98410805
Minimum46
Maximum1185.085932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:34.945891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile55.71428571
Q158
median69
Q386
95-th percentile305
Maximum1185.085932
Range1139.085932
Interquartile range (IQR)28

Descriptive statistics

Standard deviation86.53136174
Coefficient of variation (CV)0.8831162875
Kurtosis26.72274289
Mean97.98410805
Median Absolute Deviation (MAD)17
Skewness4.456871379
Sum5452227.709
Variance7487.676564
MonotonicityNot monotonic
2023-06-05T15:15:35.386194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 12702
22.8%
68 6463
11.6%
55.71428571 5543
 
10.0%
56.28571429 4870
 
8.8%
90 3283
 
5.9%
46 2513
 
4.5%
98 1449
 
2.6%
68.66666667 1055
 
1.9%
66 1000
 
1.8%
143 978
 
1.8%
Other values (2875) 15788
28.4%
ValueCountFrequency (%)
46 2513
4.5%
54 75
 
0.1%
54.5 48
 
0.1%
55 96
 
0.2%
55.33333333 1
 
< 0.1%
ValueCountFrequency (%)
1185.085932 2
< 0.1%
1161.603687 1
< 0.1%
1131.268695 1
< 0.1%
1098.677815 1
< 0.1%
1082.750674 1
< 0.1%

bidirectional_stddev_ps
Real number (ℝ)

Distinct3058
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.34956728
Minimum0
Maximum728.1035406
Zeros26514
Zeros (%)47.6%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:35.819709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.14718317
Q33.829708431
95-th percentile123.0365799
Maximum728.1035406
Range728.1035406
Interquartile range (IQR)3.829708431

Descriptive statistics

Standard deviation89.24363012
Coefficient of variation (CV)4.180114236
Kurtosis34.17972339
Mean21.34956728
Median Absolute Deviation (MAD)3.14718317
Skewness5.729789725
Sum1187975.322
Variance7964.425517
MonotonicityNot monotonic
2023-06-05T15:15:36.252327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 26514
47.6%
3.346640106 6184
 
11.1%
3.14718317 5543
 
10.0%
4.535573676 4870
 
8.8%
4.131182236 962
 
1.7%
3.14718317 676
 
1.2%
4 588
 
1.1%
3.577708764 548
 
1.0%
3.664501525 548
 
1.0%
123.0365799 498
 
0.9%
Other values (3048) 8713
 
15.7%
ValueCountFrequency (%)
0 26514
47.6%
0.5006958946 40
 
0.1%
0.5007199428 2
 
< 0.1%
0.5007283325 2
 
< 0.1%
0.5007326011 1
 
< 0.1%
ValueCountFrequency (%)
728.1035406 1
< 0.1%
723.849159 1
< 0.1%
723.6323307 1
< 0.1%
722.2813896 1
< 0.1%
721.0381235 1
< 0.1%

bidirectional_max_ps
Real number (ℝ)

Distinct598
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.3692581
Minimum46
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:36.634799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q166
median74
Q390
95-th percentile381
Maximum1514
Range1468
Interquartile range (IQR)24

Descriptive statistics

Standard deviation238.5876851
Coefficient of variation (CV)1.711910419
Kurtosis24.2479928
Mean139.3692581
Median Absolute Deviation (MAD)12
Skewness4.882020169
Sum7755063
Variance56924.08349
MonotonicityNot monotonic
2023-06-05T15:15:36.963629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 12721
22.9%
74 11172
20.1%
62 7230
13.0%
66 5496
9.9%
90 3071
 
5.5%
46 2513
 
4.5%
98 1449
 
2.6%
1514 1189
 
2.1%
143 978
 
1.8%
350 957
 
1.7%
Other values (588) 8868
15.9%
ValueCountFrequency (%)
46 2513
 
4.5%
54 75
 
0.1%
55 144
 
0.3%
60 616
 
1.1%
62 7230
13.0%
ValueCountFrequency (%)
1514 1189
2.1%
1506 9
 
< 0.1%
1498 2
 
< 0.1%
1495 1
 
< 0.1%
1494 5
 
< 0.1%

src2dst_min_ps
Real number (ℝ)

Distinct108
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.90978362
Minimum43
Maximum994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:37.274397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile54
Q154
median66
Q386
95-th percentile148
Maximum994
Range951
Interquartile range (IQR)32

Descriptive statistics

Standard deviation56.14891925
Coefficient of variation (CV)0.6691581937
Kurtosis18.56634674
Mean83.90978362
Median Absolute Deviation (MAD)12
Skewness4.063496781
Sum4669076
Variance3152.701132
MonotonicityNot monotonic
2023-06-05T15:15:37.728081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 13658
24.5%
54 13233
23.8%
86 12764
22.9%
90 3083
 
5.5%
46 2513
 
4.5%
143 1948
 
3.5%
98 1447
 
2.6%
350 776
 
1.4%
74 682
 
1.2%
60 664
 
1.2%
Other values (98) 4876
 
8.8%
ValueCountFrequency (%)
43 48
 
0.1%
46 2513
 
4.5%
54 13233
23.8%
55 144
 
0.3%
58 2
 
< 0.1%
ValueCountFrequency (%)
994 1
 
< 0.1%
590 11
< 0.1%
512 1
 
< 0.1%
467 1
 
< 0.1%
453 23
< 0.1%

src2dst_mean_ps
Real number (ℝ)

Distinct2036
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.41309273
Minimum46
Maximum1496.22811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:38.154413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile56
Q158
median69
Q386
95-th percentile188.6589744
Maximum1496.22811
Range1450.22811
Interquartile range (IQR)28

Descriptive statistics

Standard deviation83.44878392
Coefficient of variation (CV)0.8933307044
Kurtosis63.05069874
Mean93.41309273
Median Absolute Deviation (MAD)17
Skewness6.473124106
Sum5197878.132
Variance6963.699538
MonotonicityNot monotonic
2023-06-05T15:15:38.588140image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 12709
22.8%
68 8811
15.8%
56 5543
10.0%
57 4870
 
8.8%
90 3081
 
5.5%
46 2513
 
4.5%
143 1944
 
3.5%
98 1449
 
2.6%
68.66666667 1041
 
1.9%
350 776
 
1.4%
Other values (2026) 12907
23.2%
ValueCountFrequency (%)
46 2513
4.5%
54 75
 
0.1%
55 144
 
0.3%
55.6 1
 
< 0.1%
56 5543
10.0%
ValueCountFrequency (%)
1496.22811 2
< 0.1%
1456.585366 1
< 0.1%
1433.402062 1
< 0.1%
1432.439153 1
< 0.1%
1411.920915 1
< 0.1%

src2dst_stddev_ps
Real number (ℝ)

Distinct2131
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.13110445
Minimum0
Maximum1018.233765
Zeros28515
Zeros (%)51.2%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:39.036250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile26.31349464
Maximum1018.233765
Range1018.233765
Interquartile range (IQR)4

Descriptive statistics

Standard deviation68.01111404
Coefficient of variation (CV)5.179390225
Kurtosis64.67002064
Mean13.13110445
Median Absolute Deviation (MAD)0
Skewness7.801309051
Sum730667.1761
Variance4625.511633
MonotonicityNot monotonic
2023-06-05T15:15:39.480750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28515
51.2%
4 8408
 
15.1%
4 5543
 
10.0%
6 4871
 
8.8%
4.618802154 1021
 
1.8%
5.656854249 734
 
1.3%
3.577708764 621
 
1.1%
4.38178046 551
 
1.0%
2.828427125 391
 
0.7%
74.95331881 328
 
0.6%
Other values (2121) 4661
 
8.4%
ValueCountFrequency (%)
0 28515
51.2%
0.5913770168 1
 
< 0.1%
0.6859943406 1
 
< 0.1%
0.7302967433 1
 
< 0.1%
0.755928946 1
 
< 0.1%
ValueCountFrequency (%)
1018.233765 1
< 0.1%
747.5126755 1
< 0.1%
734.7095987 1
< 0.1%
730.2897446 1
< 0.1%
729.1732598 1
< 0.1%

src2dst_max_ps
Real number (ℝ)

Distinct623
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.6560456
Minimum46
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:39.908726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile60
Q166
median74
Q386
95-th percentile350
Maximum1514
Range1468
Interquartile range (IQR)20

Descriptive statistics

Standard deviation181.563285
Coefficient of variation (CV)1.543170044
Kurtosis42.66857268
Mean117.6560456
Median Absolute Deviation (MAD)12
Skewness6.270673132
Sum6546853
Variance32965.22646
MonotonicityNot monotonic
2023-06-05T15:15:40.550029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 12718
22.9%
74 11810
21.2%
62 7237
13.0%
66 5512
9.9%
90 3071
 
5.5%
46 2513
 
4.5%
143 1962
 
3.5%
98 1446
 
2.6%
70 1104
 
2.0%
350 835
 
1.5%
Other values (613) 7436
13.4%
ValueCountFrequency (%)
46 2513
 
4.5%
54 75
 
0.1%
55 144
 
0.3%
60 616
 
1.1%
62 7237
13.0%
ValueCountFrequency (%)
1514 610
1.1%
1506 5
 
< 0.1%
1498 1
 
< 0.1%
1495 1
 
< 0.1%
1494 2
 
< 0.1%

dst2src_min_ps
Real number (ℝ)

Distinct50
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.00436705
Minimum0
Maximum506
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:40.981538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median54
Q366
95-th percentile98
Maximum506
Range506
Interquartile range (IQR)66

Descriptive statistics

Standard deviation55.25907989
Coefficient of variation (CV)1.227860395
Kurtosis13.22416887
Mean45.00436705
Median Absolute Deviation (MAD)36
Skewness2.985153588
Sum2504223
Variance3053.56591
MonotonicityNot monotonic
2023-06-05T15:15:41.423609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
54 13009
23.4%
66 12769
22.9%
90 2385
 
4.3%
98 1357
 
2.4%
58 747
 
1.3%
317 590
 
1.1%
135 316
 
0.6%
327 232
 
0.4%
102 219
 
0.4%
Other values (40) 1360
 
2.4%
ValueCountFrequency (%)
0 22660
40.7%
43 48
 
0.1%
54 13009
23.4%
56 1
 
< 0.1%
58 747
 
1.3%
ValueCountFrequency (%)
506 1
< 0.1%
452 2
< 0.1%
396 2
< 0.1%
381 2
< 0.1%
375 2
< 0.1%

dst2src_mean_ps
Real number (ℝ)

Distinct2193
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.85331819
Minimum0
Maximum1482.047328
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:41.848490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median55.33333333
Q368
95-th percentile162.815942
Maximum1482.047328
Range1482.047328
Interquartile range (IQR)68

Descriptive statistics

Standard deviation106.1382465
Coefficient of variation (CV)1.834609489
Kurtosis60.49133973
Mean57.85331819
Median Absolute Deviation (MAD)42.66666667
Skewness6.544273534
Sum3219190.037
Variance11265.32737
MonotonicityNot monotonic
2023-06-05T15:15:42.280832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
55.33333333 11115
20.0%
68 7022
 
12.6%
90 2386
 
4.3%
98 1354
 
2.4%
66 1249
 
2.2%
70 1157
 
2.1%
67.33333333 790
 
1.4%
58 750
 
1.3%
68.66666667 729
 
1.3%
Other values (2183) 6432
 
11.6%
ValueCountFrequency (%)
0 22660
40.7%
54 445
 
0.8%
54.72727273 1
 
< 0.1%
54.8 4
 
< 0.1%
54.85714286 1
 
< 0.1%
ValueCountFrequency (%)
1482.047328 1
< 0.1%
1479.712963 1
< 0.1%
1472.297143 1
< 0.1%
1469.846154 1
< 0.1%
1464.574627 1
< 0.1%

dst2src_stddev_ps
Real number (ℝ)

Distinct2218
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.87152379
Minimum0
Maximum745.4010106
Zeros31430
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:42.715052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.309401077
95-th percentile8.318631763
Maximum745.4010106
Range745.4010106
Interquartile range (IQR)2.309401077

Descriptive statistics

Standard deviation79.00774116
Coefficient of variation (CV)5.312686333
Kurtosis45.70568755
Mean14.87152379
Median Absolute Deviation (MAD)0
Skewness6.637857802
Sum827511.0695
Variance6242.223164
MonotonicityNot monotonic
2023-06-05T15:15:43.146031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31430
56.5%
2.309401077 11115
 
20.0%
2.828427125 6923
 
12.4%
5.656854249 947
 
1.7%
2.309401077 790
 
1.4%
2.309401077 486
 
0.9%
6.92820323 421
 
0.8%
4.618802154 296
 
0.5%
10.50714043 112
 
0.2%
308.5546924 70
 
0.1%
Other values (2208) 3054
 
5.5%
ValueCountFrequency (%)
0 31430
56.5%
0.7612788284 1
 
< 0.1%
0.8866830869 1
 
< 0.1%
0.8866830869 1
 
< 0.1%
0.9428090416 1
 
< 0.1%
ValueCountFrequency (%)
745.4010106 1
< 0.1%
741.9907585 1
< 0.1%
733.5978917 1
< 0.1%
730.9474445 1
< 0.1%
728.6032702 1
< 0.1%

dst2src_max_ps
Real number (ℝ)

Distinct552
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.10178995
Minimum0
Maximum1514
Zeros22660
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:43.584095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median58
Q370
95-th percentile317
Maximum1514
Range1514
Interquartile range (IQR)70

Descriptive statistics

Standard deviation216.6621086
Coefficient of variation (CV)2.576189029
Kurtosis31.67421842
Mean84.10178995
Median Absolute Deviation (MAD)40
Skewness5.489350284
Sum4679760
Variance46942.4693
MonotonicityNot monotonic
2023-06-05T15:15:44.013329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22660
40.7%
58 11895
21.4%
70 9097
16.3%
90 2385
 
4.3%
74 1422
 
2.6%
98 1353
 
2.4%
66 1261
 
2.3%
1514 828
 
1.5%
317 596
 
1.1%
54 445
 
0.8%
Other values (542) 3702
 
6.7%
ValueCountFrequency (%)
0 22660
40.7%
54 445
 
0.8%
58 11895
21.4%
60 3
 
< 0.1%
61 27
 
< 0.1%
ValueCountFrequency (%)
1514 828
1.5%
1506 4
 
< 0.1%
1500 1
 
< 0.1%
1498 1
 
< 0.1%
1494 5
 
< 0.1%

bidirectional_min_piat_ms
Real number (ℝ)

Distinct2089
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3301.627435
Minimum0
Maximum119989
Zeros31630
Zeros (%)56.8%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:44.438409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile1010
Maximum119989
Range119989
Interquartile range (IQR)2

Descriptive statistics

Standard deviation18813.92058
Coefficient of variation (CV)5.698377831
Kurtosis32.75683235
Mean3301.627435
Median Absolute Deviation (MAD)0
Skewness5.861047019
Sum183715757
Variance353963607.7
MonotonicityNot monotonic
2023-06-05T15:15:44.888554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31630
56.8%
1 9473
 
17.0%
2 2494
 
4.5%
3 598
 
1.1%
307 312
 
0.6%
1010 302
 
0.5%
209 196
 
0.4%
102 185
 
0.3%
4 182
 
0.3%
145 176
 
0.3%
Other values (2079) 10096
 
18.1%
ValueCountFrequency (%)
0 31630
56.8%
1 9473
 
17.0%
2 2494
 
4.5%
3 598
 
1.1%
4 182
 
0.3%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%
Distinct19738
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4338.263962
Minimum0
Maximum119989
Zeros17333
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:45.313281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median220.225
Q31165.2
95-th percentile11216.85833
Maximum119989
Range119989
Interquartile range (IQR)1165.2

Descriptive statistics

Standard deviation19008.09375
Coefficient of variation (CV)4.38149774
Kurtosis30.26641043
Mean4338.263962
Median Absolute Deviation (MAD)220.225
Skewness5.587051151
Sum241398359.9
Variance361307627.9
MonotonicityNot monotonic
2023-06-05T15:15:45.764450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17333
31.1%
145 178
 
0.3%
1010 156
 
0.3%
2 153
 
0.3%
1010.5 148
 
0.3%
153 129
 
0.2%
197 127
 
0.2%
228 117
 
0.2%
154 107
 
0.2%
1 101
 
0.2%
Other values (19728) 37095
66.7%
ValueCountFrequency (%)
0 17333
31.1%
1 101
 
0.2%
1.333333333 1
 
< 0.1%
1.5 1
 
< 0.1%
1.555555556 1
 
< 0.1%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%
Distinct29333
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1720.266878
Minimum0
Maximum81606.48651
Zeros22748
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:46.210956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median100.089348
Q32431.694423
95-th percentile5111.675038
Maximum81606.48651
Range81606.48651
Interquartile range (IQR)2431.694423

Descriptive statistics

Standard deviation4444.033123
Coefficient of variation (CV)2.583339354
Kurtosis63.63261495
Mean1720.266878
Median Absolute Deviation (MAD)100.089348
Skewness6.706940979
Sum95722530.14
Variance19749430.4
MonotonicityNot monotonic
2023-06-05T15:15:46.648531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22748
40.9%
0.7071067812 196
 
0.4%
1.414213562 132
 
0.2%
227.4760061 65
 
0.1%
2.121320344 59
 
0.1%
99.70205615 37
 
0.1%
101.1162697 37
 
0.1%
1 36
 
0.1%
2 32
 
0.1%
2.828427125 28
 
0.1%
Other values (29323) 32274
58.0%
ValueCountFrequency (%)
0 22748
40.9%
0.3333333333 2
 
< 0.1%
0.4409585518 4
 
< 0.1%
0.5 2
 
< 0.1%
0.5773502692 15
 
< 0.1%
ValueCountFrequency (%)
81606.48651 1
< 0.1%
79552.34131 1
< 0.1%
79453.34636 1
< 0.1%
78082.97342 1
< 0.1%
76653.20351 1
< 0.1%

bidirectional_max_piat_ms
Real number (ℝ)

Distinct11116
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7554.005086
Minimum0
Maximum119989
Zeros17333
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:46.950183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median576
Q36045
95-th percentile39234.7
Maximum119989
Range119989
Interquartile range (IQR)6045

Descriptive statistics

Standard deviation21167.29955
Coefficient of variation (CV)2.802129375
Kurtosis18.64241727
Mean7554.005086
Median Absolute Deviation (MAD)576
Skewness4.333924326
Sum420335059
Variance448054570.3
MonotonicityNot monotonic
2023-06-05T15:15:47.241580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17333
31.1%
144 834
 
1.5%
1011 258
 
0.5%
145 246
 
0.4%
1012 220
 
0.4%
143 204
 
0.4%
106 202
 
0.4%
1010 176
 
0.3%
5 159
 
0.3%
1013 157
 
0.3%
Other values (11106) 35855
64.4%
ValueCountFrequency (%)
0 17333
31.1%
1 99
 
0.2%
2 116
 
0.2%
3 142
 
0.3%
4 103
 
0.2%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%

src2dst_min_piat_ms
Real number (ℝ)

Distinct3718
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3831.96828
Minimum0
Maximum119989
Zeros23044
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:47.603292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q381
95-th percentile3656
Maximum119989
Range119989
Interquartile range (IQR)81

Descriptive statistics

Standard deviation19220.71147
Coefficient of variation (CV)5.015884804
Kurtosis29.6339728
Mean3831.96828
Median Absolute Deviation (MAD)7
Skewness5.539754975
Sum213226043
Variance369435749.3
MonotonicityNot monotonic
2023-06-05T15:15:47.863180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23044
41.4%
3 1117
 
2.0%
10 1110
 
2.0%
9 1100
 
2.0%
11 1002
 
1.8%
12 964
 
1.7%
8 915
 
1.6%
13 896
 
1.6%
4 816
 
1.5%
1 813
 
1.5%
Other values (3708) 23867
42.9%
ValueCountFrequency (%)
0 23044
41.4%
1 813
 
1.5%
2 535
 
1.0%
3 1117
 
2.0%
4 816
 
1.5%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%

src2dst_mean_piat_ms
Real number (ℝ)

Distinct16482
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5137.347282
Minimum0
Maximum119989
Zeros20436
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:48.121918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median318
Q32191.333333
95-th percentile14766.62708
Maximum119989
Range119989
Interquartile range (IQR)2191.333333

Descriptive statistics

Standard deviation19468.3303
Coefficient of variation (CV)3.789568668
Kurtosis26.88461607
Mean5137.347282
Median Absolute Deviation (MAD)318
Skewness5.23608291
Sum285862552.2
Variance379015884.5
MonotonicityNot monotonic
2023-06-05T15:15:48.566495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20436
36.7%
1010 156
 
0.3%
1010.5 146
 
0.3%
1011 107
 
0.2%
1001 105
 
0.2%
104 99
 
0.2%
1 97
 
0.2%
105 88
 
0.2%
103 81
 
0.1%
102.3333333 80
 
0.1%
Other values (16472) 34249
61.6%
ValueCountFrequency (%)
0 20436
36.7%
1 97
 
0.2%
1.5 1
 
< 0.1%
2 69
 
0.1%
2.5 1
 
< 0.1%
ValueCountFrequency (%)
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
 
< 0.1%
119985 1
 
< 0.1%
119980 3
< 0.1%

src2dst_stddev_piat_ms
Real number (ℝ)

Distinct25508
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1826.243764
Minimum0
Maximum84221.36739
Zeros25299
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:49.004766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.184210836
Q33136.769636
95-th percentile6071.639639
Maximum84221.36739
Range84221.36739
Interquartile range (IQR)3136.769636

Descriptive statistics

Standard deviation4290.97776
Coefficient of variation (CV)2.349619391
Kurtosis71.21436227
Mean1826.243764
Median Absolute Deviation (MAD)6.184210836
Skewness6.803252196
Sum101619508
Variance18412490.14
MonotonicityNot monotonic
2023-06-05T15:15:49.644799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25299
45.5%
0.7071067812 477
 
0.9%
1.414213562 317
 
0.6%
2.121320344 151
 
0.3%
2.828427125 94
 
0.2%
4.949747468 78
 
0.1%
4.242640687 66
 
0.1%
1 65
 
0.1%
3.535533906 57
 
0.1%
5.656854249 55
 
0.1%
Other values (25498) 28985
52.1%
ValueCountFrequency (%)
0 25299
45.5%
0.3333333333 1
 
< 0.1%
0.5 10
 
< 0.1%
0.5 36
 
0.1%
0.5773502692 15
 
< 0.1%
ValueCountFrequency (%)
84221.36739 1
< 0.1%
84030.44856 1
< 0.1%
81436.78088 1
< 0.1%
79552.34131 1
< 0.1%
78082.97342 1
< 0.1%

src2dst_max_piat_ms
Real number (ℝ)

Distinct11273
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7582.837503
Minimum0
Maximum120118
Zeros20436
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:50.049613image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median635
Q36063
95-th percentile39429
Maximum120118
Range120118
Interquartile range (IQR)6063

Descriptive statistics

Standard deviation21178.26189
Coefficient of variation (CV)2.792920445
Kurtosis18.5965047
Mean7582.837503
Median Absolute Deviation (MAD)635
Skewness4.328723769
Sum421939410
Variance448518776.9
MonotonicityNot monotonic
2023-06-05T15:15:50.454942image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20436
36.7%
1011 227
 
0.4%
152 223
 
0.4%
106 187
 
0.3%
1010 157
 
0.3%
1001 156
 
0.3%
105 139
 
0.2%
1012 128
 
0.2%
6 120
 
0.2%
1002 118
 
0.2%
Other values (11263) 33753
60.7%
ValueCountFrequency (%)
0 20436
36.7%
1 96
 
0.2%
2 71
 
0.1%
3 42
 
0.1%
4 93
 
0.2%
ValueCountFrequency (%)
120118 1
< 0.1%
119989 2
< 0.1%
119988 2
< 0.1%
119987 1
< 0.1%
119985 1
< 0.1%

dst2src_min_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct4347
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean989.813421
Minimum0
Maximum591145
Zeros29976
Zeros (%)53.9%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:50.862056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3140
95-th percentile5530.85
Maximum591145
Range591145
Interquartile range (IQR)140

Descriptive statistics

Standard deviation6501.834236
Coefficient of variation (CV)6.568747299
Kurtosis3042.373957
Mean989.813421
Median Absolute Deviation (MAD)0
Skewness40.15911415
Sum55077178
Variance42273848.44
MonotonicityNot monotonic
2023-06-05T15:15:51.299309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29976
53.9%
8 762
 
1.4%
7 757
 
1.4%
6 755
 
1.4%
9 720
 
1.3%
3 704
 
1.3%
10 689
 
1.2%
5 621
 
1.1%
4 589
 
1.1%
11 513
 
0.9%
Other values (4337) 19558
35.1%
ValueCountFrequency (%)
0 29976
53.9%
1 484
 
0.9%
2 350
 
0.6%
3 704
 
1.3%
4 589
 
1.1%
ValueCountFrequency (%)
591145 1
< 0.1%
590885 1
< 0.1%
472686 1
< 0.1%
236338 1
< 0.1%
197140 1
< 0.1%

dst2src_mean_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct12743
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2264.862158
Minimum0
Maximum591145
Zeros27306
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:51.566161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.75
Q33036
95-th percentile6206
Maximum591145
Range591145
Interquartile range (IQR)3036

Descriptive statistics

Standard deviation9662.316196
Coefficient of variation (CV)4.266182894
Kurtosis1186.463289
Mean2264.862158
Median Absolute Deviation (MAD)4.75
Skewness27.27918207
Sum126025989.9
Variance93360354.27
MonotonicityNot monotonic
2023-06-05T15:15:51.814121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27306
49.1%
1001 109
 
0.2%
155 91
 
0.2%
146 85
 
0.2%
4.5 82
 
0.1%
156 82
 
0.1%
1008 79
 
0.1%
147 79
 
0.1%
148 76
 
0.1%
1000 73
 
0.1%
Other values (12733) 27582
49.6%
ValueCountFrequency (%)
0 27306
49.1%
0.3333333333 1
 
< 0.1%
0.375 1
 
< 0.1%
0.5 1
 
< 0.1%
1 17
 
< 0.1%
ValueCountFrequency (%)
591145 1
< 0.1%
590885 1
< 0.1%
499291.6667 1
< 0.1%
472691.3333 1
< 0.1%
472686 1
< 0.1%

dst2src_stddev_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct11349
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1629.115748
Minimum0
Maximum484430.9371
Zeros36326
Zeros (%)65.3%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:52.135565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31250.150472
95-th percentile6572.557531
Maximum484430.9371
Range484430.9371
Interquartile range (IQR)1250.150472

Descriptive statistics

Standard deviation6420.478129
Coefficient of variation (CV)3.941081619
Kurtosis1438.226065
Mean1629.115748
Median Absolute Deviation (MAD)0
Skewness29.81418431
Sum90650516.66
Variance41222539.4
MonotonicityNot monotonic
2023-06-05T15:15:52.583430image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36326
65.3%
0.7071067812 297
 
0.5%
1.414213562 168
 
0.3%
2.121320344 95
 
0.2%
2.828427125 68
 
0.1%
3.535533906 61
 
0.1%
5.656854249 59
 
0.1%
4.242640687 57
 
0.1%
1 42
 
0.1%
4.949747468 40
 
0.1%
Other values (11339) 18431
33.1%
ValueCountFrequency (%)
0 36326
65.3%
0.3333333333 1
 
< 0.1%
0.4409585518 1
 
< 0.1%
0.5 11
 
< 0.1%
0.5 35
 
0.1%
ValueCountFrequency (%)
484430.9371 1
< 0.1%
371016.5817 1
< 0.1%
306327.4519 1
< 0.1%
297417.4973 1
< 0.1%
279738.4932 1
< 0.1%

dst2src_max_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct9276
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3908.005733
Minimum0
Maximum985470
Zeros27306
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:53.025745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q35696
95-th percentile10374
Maximum985470
Range985470
Interquartile range (IQR)5696

Descriptive statistics

Standard deviation17174.88244
Coefficient of variation (CV)4.394794586
Kurtosis972.9326606
Mean3908.005733
Median Absolute Deviation (MAD)7
Skewness25.8585379
Sum217457071
Variance294976586.8
MonotonicityNot monotonic
2023-06-05T15:15:53.473402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27306
49.1%
1001 159
 
0.3%
6 133
 
0.2%
1002 118
 
0.2%
7 117
 
0.2%
8 107
 
0.2%
4 103
 
0.2%
155 97
 
0.2%
5 95
 
0.2%
1008 94
 
0.2%
Other values (9266) 27315
49.1%
ValueCountFrequency (%)
0 27306
49.1%
1 20
 
< 0.1%
2 4
 
< 0.1%
3 57
 
0.1%
4 103
 
0.2%
ValueCountFrequency (%)
985470 1
< 0.1%
866811 1
< 0.1%
749271 1
< 0.1%
748722 1
< 0.1%
748452 1
< 0.1%

bidirectional_syn_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9965494932
Minimum0
Maximum9
Zeros29139
Zeros (%)52.4%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:53.765191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.12287466
Coefficient of variation (CV)1.126762561
Kurtosis1.112630863
Mean0.9965494932
Median Absolute Deviation (MAD)0
Skewness0.7836012248
Sum55452
Variance1.260847501
MonotonicityNot monotonic
2023-06-05T15:15:54.023517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 29139
52.4%
2 22549
40.5%
3 2068
 
3.7%
1 1328
 
2.4%
4 323
 
0.6%
7 101
 
0.2%
5 56
 
0.1%
6 49
 
0.1%
8 30
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 29139
52.4%
1 1328
 
2.4%
2 22549
40.5%
3 2068
 
3.7%
4 323
 
0.6%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 30
 
0.1%
7 101
0.2%
6 49
0.1%
5 56
0.1%

bidirectional_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:54.210805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:54.371860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

bidirectional_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:54.538149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:54.697284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

bidirectional_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:54.866997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:55.030596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

bidirectional_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct397
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.43738768
Minimum0
Maximum392213
Zeros28206
Zeros (%)50.7%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:55.257178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile9
Maximum392213
Range392213
Interquartile range (IQR)6

Descriptive statistics

Standard deviation1948.756146
Coefficient of variation (CV)71.02557169
Kurtosis30458.89427
Mean27.43738768
Median Absolute Deviation (MAD)0
Skewness162.5517499
Sum1526726
Variance3797650.515
MonotonicityNot monotonic
2023-06-05T15:15:55.519556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28206
50.7%
6 12542
22.5%
5 7746
 
13.9%
1 1380
 
2.5%
4 1113
 
2.0%
7 672
 
1.2%
3 539
 
1.0%
8 258
 
0.5%
9 226
 
0.4%
2 183
 
0.3%
Other values (387) 2779
 
5.0%
ValueCountFrequency (%)
0 28206
50.7%
1 1380
 
2.5%
2 183
 
0.3%
3 539
 
1.0%
4 1113
 
2.0%
ValueCountFrequency (%)
392213 1
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%
16236 2
< 0.1%
11957 1
< 0.1%

bidirectional_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct230
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.509506865
Minimum0
Maximum31175
Zeros52108
Zeros (%)93.6%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:55.796366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum31175
Range31175
Interquartile range (IQR)0

Descriptive statistics

Standard deviation156.1428125
Coefficient of variation (CV)34.6252522
Kurtosis28675.93741
Mean4.509506865
Median Absolute Deviation (MAD)0
Skewness148.6404399
Sum250927
Variance24380.5779
MonotonicityNot monotonic
2023-06-05T15:15:56.112198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52108
93.6%
2 726
 
1.3%
1 383
 
0.7%
3 306
 
0.5%
4 268
 
0.5%
10 195
 
0.4%
5 169
 
0.3%
6 129
 
0.2%
12 127
 
0.2%
8 113
 
0.2%
Other values (220) 1120
 
2.0%
ValueCountFrequency (%)
0 52108
93.6%
1 383
 
0.7%
2 726
 
1.3%
3 306
 
0.5%
4 268
 
0.5%
ValueCountFrequency (%)
31175 1
< 0.1%
5608 1
< 0.1%
4857 2
< 0.1%
3966 1
< 0.1%
3917 1
< 0.1%

bidirectional_rst_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06225289339
Minimum0
Maximum10
Zeros52996
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:56.495313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3295322209
Coefficient of variation (CV)5.293444255
Kurtosis120.1637512
Mean0.06225289339
Median Absolute Deviation (MAD)0
Skewness8.615484125
Sum3464
Variance0.1085914846
MonotonicityNot monotonic
2023-06-05T15:15:56.844657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 52996
95.2%
1 2179
 
3.9%
2 228
 
0.4%
3 192
 
0.3%
4 26
 
< 0.1%
5 9
 
< 0.1%
6 5
 
< 0.1%
9 3
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 52996
95.2%
1 2179
 
3.9%
2 228
 
0.4%
3 192
 
0.3%
4 26
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 3
< 0.1%
8 2
 
< 0.1%
7 3
< 0.1%
6 5
< 0.1%

bidirectional_fin_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8923513766
Minimum0
Maximum9
Zeros31103
Zeros (%)55.9%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:57.135165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.041534378
Coefficient of variation (CV)1.167179661
Kurtosis0.3224576802
Mean0.8923513766
Median Absolute Deviation (MAD)0
Skewness0.6365096491
Sum49654
Variance1.08479386
MonotonicityNot monotonic
2023-06-05T15:15:57.351558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 31103
55.9%
2 22771
40.9%
1 829
 
1.5%
3 727
 
1.3%
4 118
 
0.2%
5 34
 
0.1%
8 26
 
< 0.1%
6 16
 
< 0.1%
7 12
 
< 0.1%
9 8
 
< 0.1%
ValueCountFrequency (%)
0 31103
55.9%
1 829
 
1.5%
2 22771
40.9%
3 727
 
1.3%
4 118
 
0.2%
ValueCountFrequency (%)
9 8
 
< 0.1%
8 26
< 0.1%
7 12
 
< 0.1%
6 16
< 0.1%
5 34
0.1%

src2dst_syn_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5358169794
Minimum0
Maximum7
Zeros29139
Zeros (%)52.4%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:57.703843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.6864484066
Coefficient of variation (CV)1.281124774
Kurtosis18.80876879
Mean0.5358169794
Median Absolute Deviation (MAD)0
Skewness2.766697124
Sum29815
Variance0.4712114149
MonotonicityNot monotonic
2023-06-05T15:15:58.166343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 29139
52.4%
1 24605
44.2%
2 1170
 
2.1%
3 492
 
0.9%
7 103
 
0.2%
5 55
 
0.1%
4 41
 
0.1%
6 39
 
0.1%
ValueCountFrequency (%)
0 29139
52.4%
1 24605
44.2%
2 1170
 
2.1%
3 492
 
0.9%
4 41
 
0.1%
ValueCountFrequency (%)
7 103
 
0.2%
6 39
 
0.1%
5 55
 
0.1%
4 41
 
0.1%
3 492
0.9%

src2dst_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:58.536645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:58.880157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

src2dst_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:59.223252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:15:59.553730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

src2dst_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:15:59.878243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:16:00.210843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

src2dst_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct280
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.80407591
Minimum0
Maximum271835
Zeros29610
Zeros (%)53.2%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:00.460558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5
Maximum271835
Range271835
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1314.011656
Coefficient of variation (CV)83.14384615
Kurtosis34024.04153
Mean15.80407591
Median Absolute Deviation (MAD)0
Skewness174.5861689
Sum879402
Variance1726626.632
MonotonicityNot monotonic
2023-06-05T15:16:00.837505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29610
53.2%
3 20031
36.0%
2 2073
 
3.7%
4 830
 
1.5%
1 296
 
0.5%
5 257
 
0.5%
9 251
 
0.5%
7 229
 
0.4%
8 164
 
0.3%
6 155
 
0.3%
Other values (270) 1748
 
3.1%
ValueCountFrequency (%)
0 29610
53.2%
1 296
 
0.5%
2 2073
 
3.7%
3 20031
36.0%
4 830
 
1.5%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
36078 2
< 0.1%
9702 2
< 0.1%
5875 1
< 0.1%

src2dst_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct143
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.901067501
Minimum0
Maximum6653
Zeros52749
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:01.274642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6653
Range6653
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55.65368298
Coefficient of variation (CV)29.27496418
Kurtosis5280.311151
Mean1.901067501
Median Absolute Deviation (MAD)0
Skewness63.14445639
Sum105783
Variance3097.33243
MonotonicityNot monotonic
2023-06-05T15:16:01.702975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52749
94.8%
1 985
 
1.8%
2 366
 
0.7%
3 293
 
0.5%
5 177
 
0.3%
8 148
 
0.3%
4 137
 
0.2%
30 63
 
0.1%
7 47
 
0.1%
10 36
 
0.1%
Other values (133) 643
 
1.2%
ValueCountFrequency (%)
0 52749
94.8%
1 985
 
1.8%
2 366
 
0.7%
3 293
 
0.5%
4 137
 
0.2%
ValueCountFrequency (%)
6653 1
< 0.1%
3861 1
< 0.1%
3363 1
< 0.1%
3177 1
< 0.1%
2903 1
< 0.1%

src2dst_rst_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03500826684
Minimum0
Maximum10
Zeros54150
Zeros (%)97.3%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:02.102707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.250076059
Coefficient of variation (CV)7.143343031
Kurtosis223.6568759
Mean0.03500826684
Median Absolute Deviation (MAD)0
Skewness11.7723867
Sum1948
Variance0.06253803526
MonotonicityNot monotonic
2023-06-05T15:16:02.327646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 54150
97.3%
1 1248
 
2.2%
3 119
 
0.2%
2 99
 
0.2%
4 16
 
< 0.1%
6 4
 
< 0.1%
5 3
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 54150
97.3%
1 1248
 
2.2%
2 99
 
0.2%
3 119
 
0.2%
4 16
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
8 2
< 0.1%
7 1
 
< 0.1%
6 4
< 0.1%

src2dst_fin_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4381604486
Minimum0
Maximum9
Zeros31806
Zeros (%)57.2%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:02.517337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5446181409
Coefficient of variation (CV)1.242965089
Kurtosis25.21483767
Mean0.4381604486
Median Absolute Deviation (MAD)0
Skewness2.224006618
Sum24381
Variance0.2966089194
MonotonicityNot monotonic
2023-06-05T15:16:02.762359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 31806
57.2%
1 23561
42.3%
2 213
 
0.4%
8 24
 
< 0.1%
3 18
 
< 0.1%
9 8
 
< 0.1%
5 5
 
< 0.1%
7 3
 
< 0.1%
4 3
 
< 0.1%
6 3
 
< 0.1%
ValueCountFrequency (%)
0 31806
57.2%
1 23561
42.3%
2 213
 
0.4%
3 18
 
< 0.1%
4 3
 
< 0.1%
ValueCountFrequency (%)
9 8
 
< 0.1%
8 24
< 0.1%
7 3
 
< 0.1%
6 3
 
< 0.1%
5 5
 
< 0.1%

dst2src_syn_packets
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4607325138
Minimum0
Maximum6
Zeros31230
Zeros (%)56.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:03.003215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5445684828
Coefficient of variation (CV)1.181962346
Kurtosis-0.06876162044
Mean0.4607325138
Median Absolute Deviation (MAD)0
Skewness0.6860894241
Sum25637
Variance0.2965548325
MonotonicityNot monotonic
2023-06-05T15:16:03.267968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 31230
56.1%
1 23300
41.9%
2 1008
 
1.8%
3 105
 
0.2%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 31230
56.1%
1 23300
41.9%
2 1008
 
1.8%
3 105
 
0.2%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
3 105
 
0.2%
2 1008
 
1.8%
1 23300
41.9%
0 31230
56.1%

dst2src_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:03.637341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:16:03.968416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

dst2src_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:04.303555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:16:04.640478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

dst2src_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros55644
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:04.983482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:16:05.316621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%
ValueCountFrequency (%)
0 55644
100.0%

dst2src_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct291
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.63331177
Minimum0
Maximum120378
Zeros28392
Zeros (%)51.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:05.681809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile5
Maximum120378
Range120378
Interquartile range (IQR)3

Descriptive statistics

Standard deviation702.9223947
Coefficient of variation (CV)60.4232405
Kurtosis20073.47405
Mean11.63331177
Median Absolute Deviation (MAD)0
Skewness135.2443851
Sum647324
Variance494099.893
MonotonicityNot monotonic
2023-06-05T15:16:06.130504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28392
51.0%
3 13471
24.2%
2 8516
 
15.3%
1 1827
 
3.3%
4 516
 
0.9%
5 280
 
0.5%
6 221
 
0.4%
10 216
 
0.4%
7 198
 
0.4%
8 172
 
0.3%
Other values (281) 1835
 
3.3%
ValueCountFrequency (%)
0 28392
51.0%
1 1827
 
3.3%
2 8516
 
15.3%
3 13471
24.2%
4 516
 
0.9%
ValueCountFrequency (%)
120378 1
< 0.1%
74533 2
< 0.1%
27275 2
< 0.1%
6534 2
< 0.1%
6082 1
< 0.1%

dst2src_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct156
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.608439365
Minimum0
Maximum24522
Zeros52573
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:06.485309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24522
Range24522
Interquartile range (IQR)0

Descriptive statistics

Standard deviation120.0811748
Coefficient of variation (CV)46.03563971
Kurtosis31436.20825
Mean2.608439365
Median Absolute Deviation (MAD)0
Skewness159.4011725
Sum145144
Variance14419.48854
MonotonicityNot monotonic
2023-06-05T15:16:06.933031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52573
94.5%
1 716
 
1.3%
2 575
 
1.0%
4 292
 
0.5%
3 245
 
0.4%
5 199
 
0.4%
6 91
 
0.2%
30 64
 
0.1%
7 53
 
0.1%
8 49
 
0.1%
Other values (146) 787
 
1.4%
ValueCountFrequency (%)
0 52573
94.5%
1 716
 
1.3%
2 575
 
1.0%
3 245
 
0.4%
4 292
 
0.5%
ValueCountFrequency (%)
24522 1
< 0.1%
5530 1
< 0.1%
3911 1
< 0.1%
3665 1
< 0.1%
3476 1
< 0.1%

dst2src_rst_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02724462655
Minimum0
Maximum7
Zeros54468
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:07.310409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2109750912
Coefficient of variation (CV)7.743732175
Kurtosis163.4914744
Mean0.02724462655
Median Absolute Deviation (MAD)0
Skewness10.87160978
Sum1516
Variance0.04451048912
MonotonicityNot monotonic
2023-06-05T15:16:07.648658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 54468
97.9%
1 953
 
1.7%
2 134
 
0.2%
3 72
 
0.1%
4 10
 
< 0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 54468
97.9%
1 953
 
1.7%
2 134
 
0.2%
3 72
 
0.1%
4 10
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 2
 
< 0.1%
5 4
 
< 0.1%
4 10
 
< 0.1%
3 72
0.1%

dst2src_fin_packets
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.454190928
Minimum0
Maximum6
Zeros31439
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:08.008355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5448824391
Coefficient of variation (CV)1.199677064
Kurtosis2.03795909
Mean0.454190928
Median Absolute Deviation (MAD)0
Skewness0.9069205375
Sum25273
Variance0.2968968725
MonotonicityNot monotonic
2023-06-05T15:16:08.351219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 31439
56.5%
1 23347
42.0%
2 711
 
1.3%
3 102
 
0.2%
4 31
 
0.1%
5 10
 
< 0.1%
6 4
 
< 0.1%
ValueCountFrequency (%)
0 31439
56.5%
1 23347
42.0%
2 711
 
1.3%
3 102
 
0.2%
4 31
 
0.1%
ValueCountFrequency (%)
6 4
 
< 0.1%
5 10
 
< 0.1%
4 31
 
0.1%
3 102
 
0.2%
2 711
1.3%
Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:08.710935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length4
Mean length4.799079865
Min length3

Characters and Unicode

Total characters267040
Distinct characters45
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowDHCPV6
2nd rowDHCPV6
3rd rowICMP
4th rowHTTP
5th rowHTTP
ValueCountFrequency (%)
http 23629
42.5%
icmpv6 12860
23.1%
igmp 3169
 
5.7%
ntp 3031
 
5.4%
tls 2862
 
5.1%
bittorrent 2438
 
4.4%
icmp 1955
 
3.5%
ssdp 1303
 
2.3%
unknown 1156
 
2.1%
ubntac2 927
 
1.7%
Other values (28) 2314
 
4.2%
2023-06-05T15:16:09.507951image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 57343
21.5%
P 47701
17.9%
H 24460
9.2%
M 18352
 
6.9%
I 18060
 
6.8%
C 17144
 
6.4%
V 13750
 
5.1%
6 13157
 
4.9%
S 6462
 
2.4%
n 5944
 
2.2%
Other values (35) 44667
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 223579
83.7%
Lowercase Letter 29293
 
11.0%
Decimal Number 14084
 
5.3%
Other Punctuation 77
 
< 0.1%
Connector Punctuation 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 57343
25.6%
P 47701
21.3%
H 24460
10.9%
M 18352
 
8.2%
I 18060
 
8.1%
C 17144
 
7.7%
V 13750
 
6.1%
S 6462
 
2.9%
N 4998
 
2.2%
B 3366
 
1.5%
Other values (10) 11943
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
n 5944
20.3%
t 4894
16.7%
r 4884
16.7%
o 4301
14.7%
i 3045
10.4%
e 2462
8.4%
k 1193
 
4.1%
w 1161
 
4.0%
s 601
 
2.1%
c 601
 
2.1%
Other values (10) 207
 
0.7%
Decimal Number
ValueCountFrequency (%)
6 13157
93.4%
2 927
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 77
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 252872
94.7%
Common 14168
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 57343
22.7%
P 47701
18.9%
H 24460
9.7%
M 18352
 
7.3%
I 18060
 
7.1%
C 17144
 
6.8%
V 13750
 
5.4%
S 6462
 
2.6%
n 5944
 
2.4%
N 4998
 
2.0%
Other values (30) 38658
15.3%
Common
ValueCountFrequency (%)
6 13157
92.9%
2 927
 
6.5%
. 77
 
0.5%
_ 5
 
< 0.1%
- 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 267040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 57343
21.5%
P 47701
17.9%
H 24460
9.2%
M 18352
 
6.9%
I 18060
 
6.8%
C 17144
 
6.4%
V 13750
 
5.1%
6 13157
 
4.9%
S 6462
 
2.4%
n 5944
 
2.2%
Other values (35) 44667
16.7%
Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:09.881674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.091204802
Min length3

Characters and Unicode

Total characters283295
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowNetwork
2nd rowNetwork
3rd rowNetwork
4th rowWeb
5th rowWeb
ValueCountFrequency (%)
web 26496
47.6%
network 20185
36.3%
system 4335
 
7.8%
download 2443
 
4.4%
unspecified 1156
 
2.1%
vpn 594
 
1.1%
email 251
 
0.5%
media 67
 
0.1%
voip 58
 
0.1%
advertisement 30
 
0.1%
Other values (3) 29
 
0.1%
2023-06-05T15:16:10.635837image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 53500
18.9%
W 26496
9.4%
b 26496
9.4%
o 25170
8.9%
t 24593
8.7%
w 22640
8.0%
N 20791
 
7.3%
r 20227
 
7.1%
k 20197
 
7.1%
s 5523
 
1.9%
Other values (23) 37662
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 226334
79.9%
Uppercase Letter 56961
 
20.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 53500
23.6%
b 26496
11.7%
o 25170
11.1%
t 24593
10.9%
w 22640
10.0%
r 20227
 
8.9%
k 20197
 
8.9%
s 5523
 
2.4%
m 4617
 
2.0%
y 4335
 
1.9%
Other values (10) 19036
 
8.4%
Uppercase Letter
ValueCountFrequency (%)
W 26496
46.5%
N 20791
36.5%
S 4347
 
7.6%
D 2443
 
4.3%
U 1156
 
2.0%
P 652
 
1.1%
V 652
 
1.1%
E 251
 
0.4%
M 67
 
0.1%
I 58
 
0.1%
Other values (3) 48
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 283295
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 53500
18.9%
W 26496
9.4%
b 26496
9.4%
o 25170
8.9%
t 24593
8.7%
w 22640
8.0%
N 20791
 
7.3%
r 20227
 
7.1%
k 20197
 
7.1%
s 5523
 
1.9%
Other values (23) 37662
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 283295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 53500
18.9%
W 26496
9.4%
b 26496
9.4%
o 25170
8.9%
t 24593
8.7%
w 22640
8.0%
N 20791
 
7.3%
r 20227
 
7.1%
k 20197
 
7.1%
s 5523
 
1.9%
Other values (23) 37662
13.3%

application_is_guessed
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4644346201
Minimum0
Maximum1
Zeros29801
Zeros (%)53.6%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:11.020384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4987379813
Coefficient of variation (CV)1.073860474
Kurtosis-1.979728803
Mean0.4644346201
Median Absolute Deviation (MAD)0
Skewness0.1426266281
Sum25843
Variance0.2487395739
MonotonicityNot monotonic
2023-06-05T15:16:11.382827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 29801
53.6%
1 25843
46.4%
ValueCountFrequency (%)
0 29801
53.6%
1 25843
46.4%
ValueCountFrequency (%)
1 25843
46.4%
0 29801
53.6%

application_confidence
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.571633959
Minimum0
Maximum6
Zeros1156
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:11.567142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median6
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.514639012
Coefficient of variation (CV)0.704058434
Kurtosis-1.968213527
Mean3.571633959
Median Absolute Deviation (MAD)0
Skewness-0.0847874531
Sum198740
Variance6.32340936
MonotonicityNot monotonic
2023-06-05T15:16:11.813480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 28632
51.5%
1 25423
45.7%
0 1156
 
2.1%
3 220
 
0.4%
4 200
 
0.4%
5 13
 
< 0.1%
ValueCountFrequency (%)
0 1156
 
2.1%
1 25423
45.7%
3 220
 
0.4%
4 200
 
0.4%
5 13
 
< 0.1%
ValueCountFrequency (%)
6 28632
51.5%
5 13
 
< 0.1%
4 200
 
0.4%
3 220
 
0.4%
1 25423
45.7%

requested_server_name
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing55644
Missing (%)100.0%
Memory size869.4 KiB
Distinct9
Distinct (%)2.5%
Missing55284
Missing (%)99.4%
Memory size869.4 KiB
2023-06-05T15:16:12.073696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length17
Mean length20.10833333
Min length8

Characters and Unicode

Total characters7239
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row1,3,28,6
2nd row1,3,6,12,15,28,42
3rd row1,3,28,6
4th row1,3,6,12,15,28,42
5th row1,3,28,6
ValueCountFrequency (%)
1,3,6,12,15,28,42 111
30.8%
1,3,28,6 105
29.2%
4b7ac34b7a2bc3be70a4361bd306559d 97
26.9%
c369db2c355ad05c76f5660af3179b01 21
 
5.8%
cc847787e1803cc91adeecfc721d1fc9 14
 
3.9%
1,28,2,3,15,6,12 6
 
1.7%
18b44fb15475eaf5d93a98ebaf99a0ce 3
 
0.8%
c1af646b48427e051d73839439d32709 2
 
0.6%
89f82c1fb0224e96dbc98916d8dbda04 1
 
0.3%
2023-06-05T15:16:12.730745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 1017
14.0%
3 698
9.6%
1 663
9.2%
2 595
 
8.2%
b 541
 
7.5%
6 506
 
7.0%
4 435
 
6.0%
5 406
 
5.6%
7 398
 
5.5%
a 362
 
5.0%
Other values (7) 1618
22.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4448
61.4%
Lowercase Letter 1774
 
24.5%
Other Punctuation 1017
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 698
15.7%
1 663
14.9%
2 595
13.4%
6 506
11.4%
4 435
9.8%
5 406
9.1%
7 398
8.9%
0 280
6.3%
8 278
 
6.2%
9 189
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
b 541
30.5%
a 362
20.4%
c 362
20.4%
d 275
15.5%
e 151
 
8.5%
f 83
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 1017
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5465
75.5%
Latin 1774
 
24.5%

Most frequent character per script

Common
ValueCountFrequency (%)
, 1017
18.6%
3 698
12.8%
1 663
12.1%
2 595
10.9%
6 506
9.3%
4 435
8.0%
5 406
 
7.4%
7 398
 
7.3%
0 280
 
5.1%
8 278
 
5.1%
Latin
ValueCountFrequency (%)
b 541
30.5%
a 362
20.4%
c 362
20.4%
d 275
15.5%
e 151
 
8.5%
f 83
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7239
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 1017
14.0%
3 698
9.6%
1 663
9.2%
2 595
 
8.2%
b 541
 
7.5%
6 506
 
7.0%
4 435
 
6.0%
5 406
 
5.6%
7 398
 
5.5%
a 362
 
5.0%
Other values (7) 1618
22.4%
Distinct55
Distinct (%)8.4%
Missing54986
Missing (%)98.8%
Memory size869.4 KiB
2023-06-05T15:16:13.245022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters21056
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.5%

Sample

1st row91e914bce4ef89cc2b5fdad958d585f7
2nd row63a37e7be22df054d1f448fc0c28b98f
3rd row5397c414a9ebeaff1bf18b70ca22eaa0
4th row303951d4c50efb2e991652225a6f02b1
5th row303951d4c50efb2e991652225a6f02b1
ValueCountFrequency (%)
303951d4c50efb2e991652225a6f02b1 100
15.2%
623de93db17d313345d7ea481e7443cf 97
14.7%
7bee5c1d424b7e5f943b06983bb11422 55
 
8.4%
2de81c22ea32a57162df5cb08d4a2795 55
 
8.4%
d199ba0af2b08e204c73d6d81a1fd260 38
 
5.8%
76cc3e2d3028143b23ec18e27dbd7ca9 24
 
3.6%
364ff14b04ef93c3b4cfa429d729c0d9 21
 
3.2%
30553045c697c20ead22a41ae6655ff1 20
 
3.0%
699a80bdb17efe157c861f92c5bf5d1d 18
 
2.7%
5397c414a9ebeaff1bf18b70ca22eaa0 17
 
2.6%
Other values (45) 213
32.4%
2023-06-05T15:16:14.150909image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1909
 
9.1%
1 1664
 
7.9%
3 1639
 
7.8%
d 1497
 
7.1%
e 1425
 
6.8%
5 1424
 
6.8%
4 1379
 
6.5%
9 1344
 
6.4%
b 1262
 
6.0%
7 1223
 
5.8%
Other values (6) 6290
29.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13526
64.2%
Lowercase Letter 7530
35.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1909
14.1%
1 1664
12.3%
3 1639
12.1%
5 1424
10.5%
4 1379
10.2%
9 1344
9.9%
7 1223
9.0%
0 1070
7.9%
6 1005
7.4%
8 869
6.4%
Lowercase Letter
ValueCountFrequency (%)
d 1497
19.9%
e 1425
18.9%
b 1262
16.8%
f 1134
15.1%
c 1117
14.8%
a 1095
14.5%

Most occurring scripts

ValueCountFrequency (%)
Common 13526
64.2%
Latin 7530
35.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1909
14.1%
1 1664
12.3%
3 1639
12.1%
5 1424
10.5%
4 1379
10.2%
9 1344
9.9%
7 1223
9.0%
0 1070
7.9%
6 1005
7.4%
8 869
6.4%
Latin
ValueCountFrequency (%)
d 1497
19.9%
e 1425
18.9%
b 1262
16.8%
f 1134
15.1%
c 1117
14.8%
a 1095
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1909
 
9.1%
1 1664
 
7.9%
3 1639
 
7.8%
d 1497
 
7.1%
e 1425
 
6.8%
5 1424
 
6.8%
4 1379
 
6.5%
9 1344
 
6.4%
b 1262
 
6.0%
7 1223
 
5.8%
Other values (6) 6290
29.9%
Distinct2
Distinct (%)33.3%
Missing55638
Missing (%)> 99.9%
Memory size869.4 KiB
2023-06-05T15:16:14.567502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length85
Median length65
Mean length71.66666667
Min length65

Characters and Unicode

Total characters430
Distinct characters42
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
2nd rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
3rd rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
4th rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
5th rowMozilla/5.0 (X11; Linux x86_64; rv:43.0) Gecko/20100101 Firefox/43.0 Iceweasel/43.0.4
ValueCountFrequency (%)
mozilla/5.0 6
13.6%
gecko/20100101 6
13.6%
windows 4
9.1%
nt 4
9.1%
6.1 4
9.1%
rv:53.0 4
9.1%
firefox/53.0 4
9.1%
x11 2
 
4.5%
linux 2
 
4.5%
x86_64 2
 
4.5%
Other values (3) 6
13.6%
2023-06-05T15:16:15.385210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
 
10.2%
38
 
8.8%
1 26
 
6.0%
. 26
 
6.0%
o 22
 
5.1%
/ 20
 
4.7%
e 18
 
4.2%
i 18
 
4.2%
5 14
 
3.3%
l 14
 
3.3%
Other values (32) 190
44.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 158
36.7%
Decimal Number 124
28.8%
Other Punctuation 60
 
14.0%
Space Separator 38
 
8.8%
Uppercase Letter 36
 
8.4%
Close Punctuation 6
 
1.4%
Open Punctuation 6
 
1.4%
Connector Punctuation 2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 22
13.9%
e 18
11.4%
i 18
11.4%
l 14
 
8.9%
r 12
 
7.6%
x 10
 
6.3%
a 8
 
5.1%
c 8
 
5.1%
f 6
 
3.8%
k 6
 
3.8%
Other values (7) 36
22.8%
Uppercase Letter
ValueCountFrequency (%)
G 6
16.7%
F 6
16.7%
M 6
16.7%
W 4
11.1%
N 4
11.1%
T 4
11.1%
X 2
 
5.6%
L 2
 
5.6%
I 2
 
5.6%
Decimal Number
ValueCountFrequency (%)
0 44
35.5%
1 26
21.0%
5 14
 
11.3%
3 14
 
11.3%
4 10
 
8.1%
6 8
 
6.5%
2 6
 
4.8%
8 2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 26
43.3%
/ 20
33.3%
; 8
 
13.3%
: 6
 
10.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 236
54.9%
Latin 194
45.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 22
 
11.3%
e 18
 
9.3%
i 18
 
9.3%
l 14
 
7.2%
r 12
 
6.2%
x 10
 
5.2%
a 8
 
4.1%
c 8
 
4.1%
f 6
 
3.1%
G 6
 
3.1%
Other values (16) 72
37.1%
Common
ValueCountFrequency (%)
0 44
18.6%
38
16.1%
1 26
11.0%
. 26
11.0%
/ 20
8.5%
5 14
 
5.9%
3 14
 
5.9%
4 10
 
4.2%
6 8
 
3.4%
; 8
 
3.4%
Other values (6) 28
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
 
10.2%
38
 
8.8%
1 26
 
6.0%
. 26
 
6.0%
o 22
 
5.1%
/ 20
 
4.7%
e 18
 
4.2%
i 18
 
4.2%
5 14
 
3.3%
l 14
 
3.3%
Other values (32) 190
44.2%
Distinct20
Distinct (%)1.6%
Missing54429
Missing (%)97.8%
Memory size869.4 KiB
2023-06-05T15:16:15.799028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length24
Mean length13.97283951
Min length1

Characters and Unicode

Total characters16977
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.3%

Sample

1st rowtext/javascript
2nd rowapplication/javascript
3rd rowimage/gif
4th rowimage/gif
5th rowapplication/ocsp-response
ValueCountFrequency (%)
image/gif 249
20.6%
application/javascript 179
14.8%
text/html 162
13.4%
text/javascript 141
11.7%
application/json 115
9.5%
image/jpeg 101
8.3%
application/x-javascript 100
8.3%
image/png 45
 
3.7%
text/plain 32
 
2.6%
text/css 30
 
2.5%
Other values (9) 56
 
4.6%
2023-06-05T15:16:16.525611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2126
12.5%
i 1954
11.5%
t 1768
 
10.4%
p 1482
 
8.7%
/ 1210
 
7.1%
e 915
 
5.4%
c 897
 
5.3%
g 809
 
4.8%
s 665
 
3.9%
n 659
 
3.9%
Other values (16) 4492
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15601
91.9%
Other Punctuation 1212
 
7.1%
Dash Punctuation 129
 
0.8%
Decimal Number 21
 
0.1%
Math Symbol 9
 
0.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2126
13.6%
i 1954
12.5%
t 1768
11.3%
p 1482
9.5%
e 915
 
5.9%
c 897
 
5.7%
g 809
 
5.2%
s 665
 
4.3%
n 659
 
4.2%
j 636
 
4.1%
Other values (10) 3690
23.7%
Other Punctuation
ValueCountFrequency (%)
/ 1210
99.8%
. 2
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Decimal Number
ValueCountFrequency (%)
2 21
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15601
91.9%
Common 1376
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2126
13.6%
i 1954
12.5%
t 1768
11.3%
p 1482
9.5%
e 915
 
5.9%
c 897
 
5.7%
g 809
 
5.2%
s 665
 
4.3%
n 659
 
4.2%
j 636
 
4.1%
Other values (10) 3690
23.7%
Common
ValueCountFrequency (%)
/ 1210
87.9%
- 129
 
9.4%
2 21
 
1.5%
+ 9
 
0.7%
5
 
0.4%
. 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2126
12.5%
i 1954
11.5%
t 1768
 
10.4%
p 1482
 
8.7%
/ 1210
 
7.1%
e 915
 
5.4%
c 897
 
5.3%
g 809
 
4.8%
s 665
 
3.9%
n 659
 
3.9%
Other values (16) 4492
26.5%

label
Real number (ℝ)

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size869.4 KiB
2023-06-05T15:16:16.902895image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum55644
Variance0
MonotonicityIncreasing
2023-06-05T15:16:17.236415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 55644
100.0%
ValueCountFrequency (%)
1 55644
100.0%
ValueCountFrequency (%)
1 55644
100.0%